paper_id uint32 | title string | authors list | cvf_url string | pdf_url string | supp_url string | arxiv_id string | arxiv_id_source string | bibtex large_string | abstract large_string | embedding list |
|---|---|---|---|---|---|---|---|---|---|---|
0 | Ask Your Neurons: A Neural-Based Approach to Answering Questions About Images | [
"Mateusz Malinowski",
"Marcus Rohrbach",
"Mario Fritz"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Malinowski_Ask_Your_Neurons_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Malinowski_Ask_Your_Neurons_ICCV_2015_paper.pdf | null | 1505.01121 | title_snapshot | @InProceedings{Malinowski_2015_ICCV,author = {Malinowski, Mateusz and Rohrbach, Marcus and Fritz, Mario},title = {Ask Your Neurons: A Neural-Based Approach to Answering Questions About Images},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | We address a question answering task on real-world images that is set up as a Visual Turing Test. By combining latest advances in image representation and natural language processing, we propose Neural-Image-QA, an end-to-end formulation to this problem for which all parts are trained jointly. In contrast to previous e... | [
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1 | Segment-Phrase Table for Semantic Segmentation, Visual Entailment and Paraphrasing | [
"Hamid Izadinia",
"Fereshteh Sadeghi",
"Santosh K. Divvala",
"Hannaneh Hajishirzi",
"Yejin Choi",
"Ali Farhadi"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Izadinia_Segment-Phrase_Table_for_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Izadinia_Segment-Phrase_Table_for_ICCV_2015_paper.pdf | null | 1509.08075 | title_snapshot | @InProceedings{Izadinia_2015_ICCV,author = {Izadinia, Hamid and Sadeghi, Fereshteh and Divvala, Santosh K. and Hajishirzi, Hannaneh and Choi, Yejin and Farhadi, Ali},title = {Segment-Phrase Table for Semantic Segmentation, Visual Entailment and Paraphrasing},booktitle = {Proceedings of the IEEE International Conference... | We introduce Segment-Phrase Table (SPT), a large collection of bijective associations between textual phrases and their corresponding segmentations. Leveraging recent progress in object recognition and natural language semantics, we show how we can successfully build a high-quality segment-phrase table using minimal hu... | [
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2 | Aligning Books and Movies: Towards Story-Like Visual Explanations by Watching Movies and Reading Books | [
"Yukun Zhu",
"Ryan Kiros",
"Rich Zemel",
"Ruslan Salakhutdinov",
"Raquel Urtasun",
"Antonio Torralba",
"Sanja Fidler"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Zhu_Aligning_Books_and_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Zhu_Aligning_Books_and_ICCV_2015_paper.pdf | null | 1506.06724 | title_snapshot | @InProceedings{Zhu_2015_ICCV,author = {Zhu, Yukun and Kiros, Ryan and Zemel, Rich and Salakhutdinov, Ruslan and Urtasun, Raquel and Torralba, Antonio and Fidler, Sanja},title = {Aligning Books and Movies: Towards Story-Like Visual Explanations by Watching Movies and Reading Books},booktitle = {Proceedings of the IEEE I... | Books are a rich source of both fine-grained information, how a character, an object or a scene looks like, as well as high-level semantics, what someone is thinking, feeling and how these states evolve through a story. This paper aims to align books to their movie releases in order to provide rich descriptive explanat... | [
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3 | Learning Query and Image Similarities With Ranking Canonical Correlation Analysis | [
"Ting Yao",
"Tao Mei",
"Chong-Wah Ngo"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Yao_Learning_Query_and_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Yao_Learning_Query_and_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Yao_2015_ICCV,author = {Yao, Ting and Mei, Tao and Ngo, Chong-Wah},title = {Learning Query and Image Similarities With Ranking Canonical Correlation Analysis},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | One of the fundamental problems in image search is to learn the ranking functions, i.e., similarity between the query and image. The research on this topic has evolved through two paradigms: feature-based vector model and image ranker learning. The former relies on the image surrounding texts, while the latter learns a... | [
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4 | Learning to See by Moving | [
"Pulkit Agrawal",
"Joao Carreira",
"Jitendra Malik"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Agrawal_Learning_to_See_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Agrawal_Learning_to_See_ICCV_2015_paper.pdf | null | 1505.01596 | title_snapshot | @InProceedings{Agrawal_2015_ICCV,author = {Agrawal, Pulkit and Carreira, Joao and Malik, Jitendra},title = {Learning to See by Moving},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | The current dominant paradigm for feature learning in computer vision relies on training neural networks for the task of object recognition using millions of hand labelled images. Is it also possible to learn features for a diverse set of visual tasks using any other form of supervision? In biology, living organisms de... | [
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5 | Object Detection Using Generalization and Efficiency Balanced Co-Occurrence Features | [
"Haoyu Ren",
"Ze-Nian Li"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Ren_Object_Detection_Using_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Ren_Object_Detection_Using_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Ren_2015_ICCV,author = {Ren, Haoyu and Li, Ze-Nian},title = {Object Detection Using Generalization and Efficiency Balanced Co-Occurrence Features},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | In this paper, we propose a high-accuracy object detector based on co-occurrence features. Firstly, we introduce three kinds of local co-occurrence features constructed by the traditional Haar, LBP, and HOG respectively. Then the boosted detectors are learned, where each weak classifier corresponds to a local image reg... | [
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6 | Mining And-Or Graphs for Graph Matching and Object Discovery | [
"Quanshi Zhang",
"Ying Nian Wu",
"Song-Chun Zhu"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Zhang_Mining_And-Or_Graphs_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Zhang_Mining_And-Or_Graphs_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Zhang_2015_ICCV,author = {Zhang, Quanshi and Wu, Ying Nian and Zhu, Song-Chun},title = {Mining And-Or Graphs for Graph Matching and Object Discovery},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | This paper reformulates the theory of graph mining on the technical basis of graph matching, and extends its scope of applications to computer vision. Given a set of attributed relational graphs (ARGs), we propose to use a hierarchical And-Or Graph (AoG) to model the pattern of maximal-size common subgraphs embedded in... | [
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7 | Pose Induction for Novel Object Categories | [
"Shubham Tulsiani",
"Joao Carreira",
"Jitendra Malik"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Tulsiani_Pose_Induction_for_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Tulsiani_Pose_Induction_for_ICCV_2015_paper.pdf | null | 1505.00066 | title_snapshot | @InProceedings{Tulsiani_2015_ICCV,author = {Tulsiani, Shubham and Carreira, Joao and Malik, Jitendra},title = {Pose Induction for Novel Object Categories},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | We address the task of predicting pose for objects of unannotated object categories from a small seed set of annotated object classes. We present a generalized classifier that can reliably induce pose given a single instance of a novel category. In case of availability of a large collection of novel instances, our appr... | [
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8 | Dynamic Texture Recognition via Orthogonal Tensor Dictionary Learning | [
"Yuhui Quan",
"Yan Huang",
"Hui Ji"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Quan_Dynamic_Texture_Recognition_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Quan_Dynamic_Texture_Recognition_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Quan_2015_ICCV,author = {Quan, Yuhui and Huang, Yan and Ji, Hui},title = {Dynamic Texture Recognition via Orthogonal Tensor Dictionary Learning},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | Dynamic textures (DTs) are video sequences with stationary properties, which exhibit repetitive patterns over space and time. This paper aims at investigating the sparse coding based approach to characterizing local DT patterns for recognition. Owing to the high dimensionality of DT sequences, existing dictionary learn... | [
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9 | Convolutional Channel Features | [
"Bin Yang",
"Junjie Yan",
"Zhen Lei",
"Stan Z. Li"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Yang_Convolutional_Channel_Features_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Yang_Convolutional_Channel_Features_ICCV_2015_paper.pdf | null | 1504.07339 | title_snapshot | @InProceedings{Yang_2015_ICCV,author = {Yang, Bin and Yan, Junjie and Lei, Zhen and Li, Stan Z.},title = {Convolutional Channel Features},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | Deep learning methods are powerful tools but often suffer from expensive computation and limited flexibility. An alternative is to combine light-weight models with deep representations. As successful cases exist in several visual problems, a unified framework is absent. In this paper, we revisit two widely used approac... | [
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10 | Local Convolutional Features With Unsupervised Training for Image Retrieval | [
"Mattis Paulin",
"Matthijs Douze",
"Zaid Harchaoui",
"Julien Mairal",
"Florent Perronin",
"Cordelia Schmid"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Paulin_Local_Convolutional_Features_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Paulin_Local_Convolutional_Features_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Paulin_2015_ICCV,author = {Paulin, Mattis and Douze, Matthijs and Harchaoui, Zaid and Mairal, Julien and Perronin, Florent and Schmid, Cordelia},title = {Local Convolutional Features With Unsupervised Training for Image Retrieval},booktitle = {Proceedings of the IEEE International Conference on Computer ... | Patch-level descriptors underlie several important computer vision tasks, such as stereo-matching or content-based image retrieval. We introduce a deep convolutional architecture that yields patch-level descriptors, as an alternative to the popular SIFT descriptor for image retrieval. The proposed family of descri... | [
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11 | RIDE: Reversal Invariant Descriptor Enhancement | [
"Lingxi Xie",
"Jingdong Wang",
"Weiyao Lin",
"Bo Zhang",
"Qi Tian"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Xie_RIDE_Reversal_Invariant_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Xie_RIDE_Reversal_Invariant_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Xie_2015_ICCV,author = {Xie, Lingxi and Wang, Jingdong and Lin, Weiyao and Zhang, Bo and Tian, Qi},title = {RIDE: Reversal Invariant Descriptor Enhancement},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | In many fine-grained object recognition datasets, image orientation (left/right) might vary from sample to sample. Since handcrafted descriptors such as SIFT are not reversal invariant, the stability of image representation based on them is consequently limited. A popular solution is to augment the datasets by adding a... | [
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12 | Discrete Tabu Search for Graph Matching | [
"Kamil Adamczewski",
"Yumin Suh",
"Kyoung Mu Lee"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Adamczewski_Discrete_Tabu_Search_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Adamczewski_Discrete_Tabu_Search_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Adamczewski_2015_ICCV,author = {Adamczewski, Kamil and Suh, Yumin and Lee, Kyoung Mu},title = {Discrete Tabu Search for Graph Matching},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | Graph matching is a fundamental problem in computer vision. In this paper, we propose a novel graph matching algorithm based on tabu search. The proposed method solves graph matching problem by casting it into an equivalent weighted maximum clique problem of the corresponding association graph, which we further penaliz... | [
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13 | Discriminative Learning of Deep Convolutional Feature Point Descriptors | [
"Edgar Simo-Serra",
"Eduard Trulls",
"Luis Ferraz",
"Iasonas Kokkinos",
"Pascal Fua",
"Francesc Moreno-Noguer"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Simo-Serra_Discriminative_Learning_of_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Simo-Serra_Discriminative_Learning_of_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Simo-Serra_2015_ICCV,author = {Simo-Serra, Edgar and Trulls, Eduard and Ferraz, Luis and Kokkinos, Iasonas and Fua, Pascal and Moreno-Noguer, Francesc},title = {Discriminative Learning of Deep Convolutional Feature Point Descriptors},booktitle = {Proceedings of the IEEE International Conference on Comput... | Deep learning has revolutionalized image-level tasks such as classification, but patch-level tasks, such as correspondence, still rely on hand-crafted features, e.g. SIFT. In this paper we use Convolutional Neural Networks (CNNs) to learn discriminant patch representations and in particular train a Siamese network with... | [
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14 | Amodal Completion and Size Constancy in Natural Scenes | [
"Abhishek Kar",
"Shubham Tulsiani",
"Joao Carreira",
"Jitendra Malik"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Kar_Amodal_Completion_and_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Kar_Amodal_Completion_and_ICCV_2015_paper.pdf | null | 1509.08147 | title_snapshot | @InProceedings{Kar_2015_ICCV,author = {Kar, Abhishek and Tulsiani, Shubham and Carreira, Joao and Malik, Jitendra},title = {Amodal Completion and Size Constancy in Natural Scenes},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | We consider the problem of enriching current object detection systems with veridical object sizes and relative depth estimates from a single image. There are several technical challenges to this, such as occlusions, lack of calibration data and the scale ambiguity between object size and distance. These have not been a... | [
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15 | Learning Where to Position Parts in 3D | [
"Marco Pedersoli",
"Tinne Tuytelaars"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Pedersoli_Learning_Where_to_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Pedersoli_Learning_Where_to_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Pedersoli_2015_ICCV,author = {Pedersoli, Marco and Tuytelaars, Tinne},title = {Learning Where to Position Parts in 3D},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | A common issue in deformable object detection is finding a good way to position the parts. This issue is even more outspoken when considering detection and pose estimation for 3D objects, where parts should be placed in a three-dimensional space. Some methods extract the 3D shape of the object from 3D CAD models. This ... | [
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16 | Query Adaptive Similarity Measure for RGB-D Object Recognition | [
"Yanhua Cheng",
"Rui Cai",
"Chi Zhang",
"Zhiwei Li",
"Xin Zhao",
"Kaiqi Huang",
"Yong Rui"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Cheng_Query_Adaptive_Similarity_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Cheng_Query_Adaptive_Similarity_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Cheng_2015_ICCV,author = {Cheng, Yanhua and Cai, Rui and Zhang, Chi and Li, Zhiwei and Zhao, Xin and Huang, Kaiqi and Rui, Yong},title = {Query Adaptive Similarity Measure for RGB-D Object Recognition},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {Decem... | This paper studies the problem of improving the top-1 accuracy of RGB-D object recognition. Despite of the impressive top-5 accuracies achieved by existing methods, their top-1 accuracies are not very satisfactory. The reasons are in two-fold: (1) existing similarity measures are sensitive to object pose and scale chan... | [
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17 | Listening With Your Eyes: Towards a Practical Visual Speech Recognition System Using Deep Boltzmann Machines | [
"Chao Sui",
"Mohammed Bennamoun",
"Roberto Togneri"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Sui_Listening_With_Your_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Sui_Listening_With_Your_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Sui_2015_ICCV,author = {Sui, Chao and Bennamoun, Mohammed and Togneri, Roberto},title = {Listening With Your Eyes: Towards a Practical Visual Speech Recognition System Using Deep Boltzmann Machines},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December... | This paper presents a novel feature learning method for visual speech recognition using Deep Boltzmann Machines (DBM). Unlike all existing visual feature extraction techniques which solely extracts features from video sequences, our method is able to explore both acoustic information and visual information to learn a b... | [
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18 | Cluster-Based Point Set Saliency | [
"Flora Ponjou Tasse",
"Jiri Kosinka",
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] | https://openaccess.thecvf.com/content_iccv_2015/html/Tasse_Cluster-Based_Point_Set_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Tasse_Cluster-Based_Point_Set_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Tasse_2015_ICCV,author = {Tasse, Flora Ponjou and Kosinka, Jiri and Dodgson, Neil},title = {Cluster-Based Point Set Saliency},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | We propose a cluster-based approach to point set saliency detection, a challenge since point sets lack topological information. A point set is first decomposed into small clusters, using fuzzy clustering. We evaluate cluster uniqueness and spatial distribution of each cluster and combine these values into a cluster sal... | [
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19 | A Comprehensive Multi-Illuminant Dataset for Benchmarking of the Intrinsic Image Algorithms | [
"Shida Beigpour",
"Andreas Kolb",
"Sven Kunz"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Beigpour_A_Comprehensive_Multi-Illuminant_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Beigpour_A_Comprehensive_Multi-Illuminant_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Beigpour_2015_ICCV,author = {Beigpour, Shida and Kolb, Andreas and Kunz, Sven},title = {A Comprehensive Multi-Illuminant Dataset for Benchmarking of the Intrinsic Image Algorithms},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | In this paper, we provide a new, real photo dataset with precise ground-truth for intrinsic image research. Prior ground-truth datasets have been restricted to rather simple illumination conditions and scene geometries, or have been enhanced using image synthesis methods. The dataset provided in this paper is based on ... | [
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20 | PatchMatch-Based Automatic Lattice Detection for Near-Regular Textures | [
"Siying Liu",
"Tian-Tsong Ng",
"Kalyan Sunkavalli",
"Minh N. Do",
"Eli Shechtman",
"Nathan Carr"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Liu_PatchMatch-Based_Automatic_Lattice_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Liu_PatchMatch-Based_Automatic_Lattice_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Liu_2015_ICCV,author = {Liu, Siying and Ng, Tian-Tsong and Sunkavalli, Kalyan and Do, Minh N. and Shechtman, Eli and Carr, Nathan},title = {PatchMatch-Based Automatic Lattice Detection for Near-Regular Textures},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},mont... | In this work, we investigate the problem of automatically inferring the lattice structure of near-regular textures (NRT) in real-world images. Our technique leverages the PatchMatch algorithm for finding k-nearest-neighbor (kNN) correspondences in an image. We use these kNNs to recover an initial estimate of the 2D wal... | [
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21 | A Data-Driven Metric for Comprehensive Evaluation of Saliency Models | [
"Jia Li",
"Changqun Xia",
"Yafei Song",
"Shu Fang",
"Xiaowu Chen"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Li_A_Data-Driven_Metric_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Li_A_Data-Driven_Metric_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Li_2015_ICCV,author = {Li, Jia and Xia, Changqun and Song, Yafei and Fang, Shu and Chen, Xiaowu},title = {A Data-Driven Metric for Comprehensive Evaluation of Saliency Models},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | In the past decades, hundreds of saliency models have been proposed for fixation prediction, along with dozens of evaluation metrics. However, existing metrics, which are often heuristically designed, may draw conflict conclusions in comparing saliency models. As a consequence, it becomes somehow confusing on the selec... | [
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22 | A Matrix Decomposition Perspective to Multiple Graph Matching | [
"Junchi Yan",
"Hongteng Xu",
"Hongyuan Zha",
"Xiaokang Yang",
"Huanxi Liu",
"Stephen Chu"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Yan_A_Matrix_Decomposition_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Yan_A_Matrix_Decomposition_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Yan_2015_ICCV,author = {Yan, Junchi and Xu, Hongteng and Zha, Hongyuan and Yang, Xiaokang and Liu, Huanxi and Chu, Stephen},title = {A Matrix Decomposition Perspective to Multiple Graph Matching},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},y... | Graph matching has a wide spectrum of real-world applications and in general is known NP-hard. In many vision tasks, one realistic problem arises for finding the global node mappings across a batch of corrupted weighted graphs. This paper is an attempt to connect graph matching, especially multi-graph matching to the m... | [
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23 | Fast and Effective L0 Gradient Minimization by Region Fusion | [
"Rang M. H. Nguyen",
"Michael S. Brown"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Nguyen_Fast_and_Effective_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Nguyen_Fast_and_Effective_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Nguyen_2015_ICCV,author = {Nguyen, Rang M. H. and Brown, Michael S.},title = {Fast and Effective L0 Gradient Minimization by Region Fusion},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | L_0 gradient minimization can be applied to an input signal to control the number of non-zero gradients. This is useful in reducing small gradients generally associated with signal noise, while preserving important signal features. In computer vision, L_0 gradient minimization has found applications in image denoisin... | [
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24 | Generic Promotion of Diffusion-Based Salient Object Detection | [
"Peng Jiang",
"Nuno Vasconcelos",
"Jingliang Peng"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Jiang_Generic_Promotion_of_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Jiang_Generic_Promotion_of_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Jiang_2015_ICCV,author = {Jiang, Peng and Vasconcelos, Nuno and Peng, Jingliang},title = {Generic Promotion of Diffusion-Based Salient Object Detection},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | In this work, we propose a generic scheme to promote any diffusion-based salient object detection algorithm by original ways to re-synthesize the diffusion matrix and construct the seed vector. We first make a novel analysis of the working mechanism of the diffusion matrix, which reveals the close relationship between ... | [
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25 | Nighttime Haze Removal With Glow and Multiple Light Colors | [
"Yu Li",
"Robby T. Tan",
"Michael S. Brown"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Li_Nighttime_Haze_Removal_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Li_Nighttime_Haze_Removal_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Li_2015_ICCV,author = {Li, Yu and Tan, Robby T. and Brown, Michael S.},title = {Nighttime Haze Removal With Glow and Multiple Light Colors},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | This paper focuses on dehazing nighttime images. Most existing dehazing methods use models that are formulated to describe haze in daytime. Daytime models assume a single uniform light color attributed to a light source not directly visible in the scene. Nighttime scenes, however, commonly include visible lights sou... | [
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26 | Conformal and Low-Rank Sparse Representation for Image Restoration | [
"Jianwei Li",
"Xiaowu Chen",
"Dongqing Zou",
"Bo Gao",
"Wei Teng"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Li_Conformal_and_Low-Rank_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Li_Conformal_and_Low-Rank_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Li_2015_ICCV,author = {Li, Jianwei and Chen, Xiaowu and Zou, Dongqing and Gao, Bo and Teng, Wei},title = {Conformal and Low-Rank Sparse Representation for Image Restoration},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | Obtaining an appropriate dictionary is the key point when sparse representation is applied to computer vision or image processing problems such as image restoration. It is expected that preserving data structure during sparse coding and dictionary learning can enhance the recovery performance. However, many existing di... | [
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27 | Patch Group Based Nonlocal Self-Similarity Prior Learning for Image Denoising | [
"Jun Xu",
"Lei Zhang",
"Wangmeng Zuo",
"David Zhang",
"Xiangchu Feng"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Xu_Patch_Group_Based_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Xu_Patch_Group_Based_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Xu_2015_ICCV,author = {Xu, Jun and Zhang, Lei and Zuo, Wangmeng and Zhang, David and Feng, Xiangchu},title = {Patch Group Based Nonlocal Self-Similarity Prior Learning for Image Denoising},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {... | Patch based image modeling has achieved a great success in low level vision such as image denoising. In particular, the use of image nonlocal self-similarity (NSS) prior, which refers to the fact that a local patch often has many nonlocal similar patches to it across the image, has significantly enhanced the denoising ... | [
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28 | Automatic Thumbnail Generation Based on Visual Representativeness and Foreground Recognizability | [
"Jingwei Huang",
"Huarong Chen",
"Bin Wang",
"Stephen Lin"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Huang_Automatic_Thumbnail_Generation_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Huang_Automatic_Thumbnail_Generation_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Huang_2015_ICCV,author = {Huang, Jingwei and Chen, Huarong and Wang, Bin and Lin, Stephen},title = {Automatic Thumbnail Generation Based on Visual Representativeness and Foreground Recognizability},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December}... | We present an automatic thumbnail generation technique based on two essential considerations: how well they visually represent the original photograph, and how well the foreground can be recognized after the cropping and downsizing steps of thumbnailing. These factors, while important for the image indexing purpose of ... | [
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29 | SALICON: Reducing the Semantic Gap in Saliency Prediction by Adapting Deep Neural Networks | [
"Xun Huang",
"Chengyao Shen",
"Xavier Boix",
"Qi Zhao"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Huang_SALICON_Reducing_the_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Huang_SALICON_Reducing_the_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Huang_2015_ICCV,author = {Huang, Xun and Shen, Chengyao and Boix, Xavier and Zhao, Qi},title = {SALICON: Reducing the Semantic Gap in Saliency Prediction by Adapting Deep Neural Networks},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2... | Saliency in Context (SALICON) is an ongoing effort that aims at understanding and predicting visual attention. Conventional saliency models typically rely on low-level image statistics to predict human fixations. While these models perform significantly better than chance, there is still a large gap between model predi... | [
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30 | A Novel Sparsity Measure for Tensor Recovery | [
"Qian Zhao",
"Deyu Meng",
"Xu Kong",
"Qi Xie",
"Wenfei Cao",
"Yao Wang",
"Zongben Xu"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Zhao_A_Novel_Sparsity_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Zhao_A_Novel_Sparsity_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Zhao_2015_ICCV,author = {Zhao, Qian and Meng, Deyu and Kong, Xu and Xie, Qi and Cao, Wenfei and Wang, Yao and Xu, Zongben},title = {A Novel Sparsity Measure for Tensor Recovery},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | In this paper, we propose a new sparsity regularizer for measuring the low-rank structure underneath a tensor. The proposed sparsity measure has a natural physical meaning which is intrinsically the size of the fundamental Kronecker basis to express the tensor. By embedding the sparsity measure into the tensor completi... | [
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31 | Oriented Object Proposals | [
"Shengfeng He",
"Rynson W.H. Lau"
] | https://openaccess.thecvf.com/content_iccv_2015/html/He_Oriented_Object_Proposals_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/He_Oriented_Object_Proposals_ICCV_2015_paper.pdf | null | null | null | @InProceedings{He_2015_ICCV,author = {He, Shengfeng and Lau, Rynson W.H.},title = {Oriented Object Proposals},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | In this paper, we propose a new approach to generate oriented object proposals (OOPs) to reduce the detection error caused by various orientations of the object. To this end, we propose to efficiently locate object regions according to pixelwise object probability, rather than measuring the objectness from a set of sam... | [
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32 | Learning Nonlinear Spectral Filters for Color Image Reconstruction | [
"Michael Moeller",
"Julia Diebold",
"Guy Gilboa",
"Daniel Cremers"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Moeller_Learning_Nonlinear_Spectral_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Moeller_Learning_Nonlinear_Spectral_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Moeller_2015_ICCV,author = {Moeller, Michael and Diebold, Julia and Gilboa, Guy and Cremers, Daniel},title = {Learning Nonlinear Spectral Filters for Color Image Reconstruction},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | This paper presents the idea of learning optimal filters for color image reconstruction based on a novel concept of nonlinear spectral image decompositions recently proposed by Guy Gilboa. We use a multiscale image decomposition approach based on total variation regularization and Bregman iterations to represent the in... | [
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33 | Beyond White: Ground Truth Colors for Color Constancy Correction | [
"Dongliang Cheng",
"Brian Price",
"Scott Cohen",
"Michael S. Brown"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Cheng_Beyond_White_Ground_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Cheng_Beyond_White_Ground_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Cheng_2015_ICCV,author = {Cheng, Dongliang and Price, Brian and Cohen, Scott and Brown, Michael S.},title = {Beyond White: Ground Truth Colors for Color Constancy Correction},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | A limitation in color constancy research is the inability to establish ground truth colors for evaluating corrected images. Many existing datasets contain images of scenes with a color chart included; however, only the chart's neutral colors (grayscale patches) are used to provide the ground truth for illumination esti... | [
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34 | RGB-Guided Hyperspectral Image Upsampling | [
"Hyeokhyen Kwon",
"Yu-Wing Tai"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Kwon_RGB-Guided_Hyperspectral_Image_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Kwon_RGB-Guided_Hyperspectral_Image_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Kwon_2015_ICCV,author = {Kwon, Hyeokhyen and Tai, Yu-Wing},title = {RGB-Guided Hyperspectral Image Upsampling},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | Hyperspectral imaging usually lack of spatial resolution due to limitations of hardware design of imaging sensors. On the contrary, latest imaging sensors capture a RGB image with resolution of multiple times larger than a hyperspectral image. In this paper, we present an algorithm to enhance and upsample the resolutio... | [
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35 | Projection Onto the Manifold of Elongated Structures for Accurate Extraction | [
"Amos Sironi",
"Vincent Lepetit",
"Pascal Fua"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Sironi_Projection_Onto_the_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Sironi_Projection_Onto_the_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Sironi_2015_ICCV,author = {Sironi, Amos and Lepetit, Vincent and Fua, Pascal},title = {Projection Onto the Manifold of Elongated Structures for Accurate Extraction},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | Detection of elongated structures in 2D images and 3D image stacks is a critical prerequisite in many applications and Machine Learning-based approaches have recently been shown to deliver superior performance. However, these methods essentially classify individual locations and do not explicitly model the str... | [
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36 | Naive Bayes Super-Resolution Forest | [
"Jordi Salvador",
"Eduardo Perez-Pellitero"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Salvador_Naive_Bayes_Super-Resolution_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Salvador_Naive_Bayes_Super-Resolution_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Salvador_2015_ICCV,author = {Salvador, Jordi and Perez-Pellitero, Eduardo},title = {Naive Bayes Super-Resolution Forest},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | This paper presents a fast, high-performance method for super resolution with external learning. The first contribution leading to the excellent performance is a bimodal tree for clustering, which successfully exploits the antipodal invariance of the coarse-to-high-res mapping of natural image patches and provides scal... | [
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37 | POP Image Fusion - Derivative Domain Image Fusion Without Reintegration | [
"Graham D. Finlayson",
"Alex E. Hayes"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Finlayson_POP_Image_Fusion_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Finlayson_POP_Image_Fusion_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Finlayson_2015_ICCV,author = {Finlayson, Graham D. and Hayes, Alex E.},title = {POP Image Fusion - Derivative Domain Image Fusion Without Reintegration},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | There are many applications where multiple images are fused to form a single summary greyscale or colour output, including computational photography (e.g. RGB-NIR), diffusion tensor imaging (medical), and remote sensing. Often, and intuitively, image fusion is carried out in the derivative domain. Here, a new composite... | [
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38 | Adaptive Spatial-Spectral Dictionary Learning for Hyperspectral Image Denoising | [
"Ying Fu",
"Antony Lam",
"Imari Sato",
"Yoichi Sato"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Fu_Adaptive_Spatial-Spectral_Dictionary_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Fu_Adaptive_Spatial-Spectral_Dictionary_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Fu_2015_ICCV,author = {Fu, Ying and Lam, Antony and Sato, Imari and Sato, Yoichi},title = {Adaptive Spatial-Spectral Dictionary Learning for Hyperspectral Image Denoising},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | Hyperspectral imaging is beneficial in a diverse range of applications from diagnostic medicine, to agriculture, to surveillance to name a few. However, hyperspectral images often times suffer from degradation due to the limited light, which introduces noise into the imaging process. In this paper, we propose an effect... | [
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39 | Fully Connected Guided Image Filtering | [
"Longquan Dai",
"Mengke Yuan",
"Feihu Zhang",
"Xiaopeng Zhang"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Dai_Fully_Connected_Guided_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Dai_Fully_Connected_Guided_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Dai_2015_ICCV,author = {Dai, Longquan and Yuan, Mengke and Zhang, Feihu and Zhang, Xiaopeng},title = {Fully Connected Guided Image Filtering},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | This paper presents a linear time fully connected guided filter by introducing the minimum spanning tree (MST) to the guided filter (GF). Since the intensity based filtering kernel of GF is apt to overly smooth edges and the fixed-shape local box support region adopted by GF is not geometric-adaptive, our filter introd... | [
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40 | Segment Graph Based Image Filtering: Fast Structure-Preserving Smoothing | [
"Feihu Zhang",
"Longquan Dai",
"Shiming Xiang",
"Xiaopeng Zhang"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Zhang_Segment_Graph_Based_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Zhang_Segment_Graph_Based_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Zhang_2015_ICCV,author = {Zhang, Feihu and Dai, Longquan and Xiang, Shiming and Zhang, Xiaopeng},title = {Segment Graph Based Image Filtering: Fast Structure-Preserving Smoothing},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | In this paper, we design a new edge-aware structure, named segment graph, to represent the image and we further develop a novel double weighted average image filter (SGF) based on the segment graph. In our SGF, we use the tree distance on the segment graph to define the internal weight function of the filtering kernel,... | [
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41 | Deep Networks for Image Super-Resolution With Sparse Prior | [
"Zhaowen Wang",
"Ding Liu",
"Jianchao Yang",
"Wei Han",
"Thomas Huang"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Wang_Deep_Networks_for_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Wang_Deep_Networks_for_ICCV_2015_paper.pdf | null | 1507.08905 | title_snapshot | @InProceedings{Wang_2015_ICCV,author = {Wang, Zhaowen and Liu, Ding and Yang, Jianchao and Han, Wei and Huang, Thomas},title = {Deep Networks for Image Super-Resolution With Sparse Prior},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | Deep learning techniques have been successfully applied in many areas of computer vision, including low-level image restoration problems. For image super-resolution, several models based on deep neural networks have been recently proposed and attained superior performance that overshadows all previous handcrafted model... | [
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42 | Convolutional Color Constancy | [
"Jonathan T. Barron"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Barron_Convolutional_Color_Constancy_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Barron_Convolutional_Color_Constancy_ICCV_2015_paper.pdf | null | 1507.00410 | title_snapshot | @InProceedings{Barron_2015_ICCV,author = {Barron, Jonathan T.},title = {Convolutional Color Constancy},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | Color constancy is the problem of inferring the color of the light that illuminated a scene, usually so that the illumination color can be removed. Because this problem is underconstrained, it is often solved by modeling the statistical regularities of the colors of natural objects and illumination. In contrast, in thi... | [
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43 | Learning Ordinal Relationships for Mid-Level Vision | [
"Daniel Zoran",
"Phillip Isola",
"Dilip Krishnan",
"William T. Freeman"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Zoran_Learning_Ordinal_Relationships_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Zoran_Learning_Ordinal_Relationships_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Zoran_2015_ICCV,author = {Zoran, Daniel and Isola, Phillip and Krishnan, Dilip and Freeman, William T.},title = {Learning Ordinal Relationships for Mid-Level Vision},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | We propose a framework that infers mid-level visual properties of an image by learning about ordinal relation- ships. Instead of estimating metric quantities directly, the system proposes pairwise relationship estimates for points in the input image. These sparse probabilistic ordinal mea- surements are globalized to c... | [
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44 | Thin Structure Estimation With Curvature Regularization | [
"Dmitrii Marin",
"Yuchen Zhong",
"Maria Drangova",
"Yuri Boykov"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Marin_Thin_Structure_Estimation_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Marin_Thin_Structure_Estimation_ICCV_2015_paper.pdf | null | 1506.04654 | title_snapshot | @InProceedings{Marin_2015_ICCV,author = {Marin, Dmitrii and Zhong, Yuchen and Drangova, Maria and Boykov, Yuri},title = {Thin Structure Estimation With Curvature Regularization},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | Many applications in vision require estimation of thin structures such as boundary edges, surfaces, roads, blood vessels, neurons, etc. Unlike most previous approaches, we simultaneously detect and delineate thin structures with sub-pixel localization and real-valued orientation estimation. This is an ill-posed problem... | [
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45 | HARF: Hierarchy-Associated Rich Features for Salient Object Detection | [
"Wenbin Zou",
"Nikos Komodakis"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Zou_HARF_Hierarchy-Associated_Rich_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Zou_HARF_Hierarchy-Associated_Rich_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Zou_2015_ICCV,author = {Zou, Wenbin and Komodakis, Nikos},title = {HARF: Hierarchy-Associated Rich Features for Salient Object Detection},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | The state-of-the-art salient object detection models are able to perform well for relatively simple scenes, yet for more complex ones, they still have difficulties in highlighting salient objects completely from background, largely due to the lack of sufficiently robust features for saliency prediction. To address such... | [
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46 | Deep Colorization | [
"Zezhou Cheng",
"Qingxiong Yang",
"Bin Sheng"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Cheng_Deep_Colorization_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Cheng_Deep_Colorization_ICCV_2015_paper.pdf | null | 1605.00075 | title_snapshot | @InProceedings{Cheng_2015_ICCV,author = {Cheng, Zezhou and Yang, Qingxiong and Sheng, Bin},title = {Deep Colorization},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | This paper investigates into the colorization problem which converts a grayscale image to a colorful version. This is a very difficult problem and normally requires manual adjustment to achieve artifact-free quality. For instance, it normally requires human-labelled color scribbles on the grayscale target image or a ca... | [
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47 | Image Matting With KL-Divergence Based Sparse Sampling | [
"Levent Karacan",
"Aykut Erdem",
"Erkut Erdem"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Karacan_Image_Matting_With_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Karacan_Image_Matting_With_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Karacan_2015_ICCV,author = {Karacan, Levent and Erdem, Aykut and Erdem, Erkut},title = {Image Matting With KL-Divergence Based Sparse Sampling},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | Previous sampling-based image matting methods typically rely on certain heuristics in collecting representative samples from known regions, and thus their performance deteriorates if the underlying assumptions are not satisfied. To alleviate this, in this paper we take an entirely new approach and formulate sampling as... | [
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48 | Intrinsic Decomposition of Image Sequences From Local Temporal Variations | [
"Pierre-Yves Laffont",
"Jean-Charles Bazin"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Laffont_Intrinsic_Decomposition_of_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Laffont_Intrinsic_Decomposition_of_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Laffont_2015_ICCV,author = {Laffont, Pierre-Yves and Bazin, Jean-Charles},title = {Intrinsic Decomposition of Image Sequences From Local Temporal Variations},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | We present a method for intrinsic image decomposition, which aims to decompose images into reflectance and shading layers. Our input is a sequence of images with varying illumination acquired by a static camera, e.g. an indoor scene with a moving light source or an outdoor timelapse. We leverage the local color variati... | [
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49 | Low-Rank Tensor Approximation With Laplacian Scale Mixture Modeling for Multiframe Image Denoising | [
"Weisheng Dong",
"Guangyu Li",
"Guangming Shi",
"Xin Li",
"Yi Ma"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Dong_Low-Rank_Tensor_Approximation_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Dong_Low-Rank_Tensor_Approximation_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Dong_2015_ICCV,author = {Dong, Weisheng and Li, Guangyu and Shi, Guangming and Li, Xin and Ma, Yi},title = {Low-Rank Tensor Approximation With Laplacian Scale Mixture Modeling for Multiframe Image Denoising},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = ... | Patch-based low-rank models have shown effective in exploiting spatial redundancy of natural images especially for the application of image denoising. However, two-dimensional low-rank model can not fully exploit the spatio-temporal correlation in larger data sets such as multispectral images and 3D MRIs. In this work,... | [
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50 | Learning Parametric Distributions for Image Super-Resolution: Where Patch Matching Meets Sparse Coding | [
"Yongbo Li",
"Weisheng Dong",
"Guangming Shi",
"Xuemei Xie"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Li_Learning_Parametric_Distributions_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Li_Learning_Parametric_Distributions_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Li_2015_ICCV,author = {Li, Yongbo and Dong, Weisheng and Shi, Guangming and Xie, Xuemei},title = {Learning Parametric Distributions for Image Super-Resolution: Where Patch Matching Meets Sparse Coding},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {Decem... | Existing approaches toward Image super-resolution (SR) is often either data-driven (e.g., based on internet-scale matching and web image retrieval) or model-based (e.g., formulated as an Maximizing a Posterior estimation problem). The former is conceptually simple yet heuristic; while the latter is constrained by the f... | [
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51 | Improving Image Restoration With Soft-Rounding | [
"Xing Mei",
"Honggang Qi",
"Bao-Gang Hu",
"Siwei Lyu"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Mei_Improving_Image_Restoration_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Mei_Improving_Image_Restoration_ICCV_2015_paper.pdf | null | 1508.05046 | title_snapshot | @InProceedings{Mei_2015_ICCV,author = {Mei, Xing and Qi, Honggang and Hu, Bao-Gang and Lyu, Siwei},title = {Improving Image Restoration With Soft-Rounding},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | Several important classes of images such as text, barcode and pattern images have the property that pixels can only take a distinct subset of values. This knowledge can benefit the restoration of such images, but it has not been widely considered in current restoration methods. In this work, we describe an effective an... | [
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52 | See the Difference: Direct Pre-Image Reconstruction and Pose Estimation by Differentiating HOG | [
"Wei-Chen Chiu",
"Mario Fritz"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Chiu_See_the_Difference_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Chiu_See_the_Difference_ICCV_2015_paper.pdf | null | 1505.00663 | title_snapshot | @InProceedings{Chiu_2015_ICCV,author = {Chiu, Wei-Chen and Fritz, Mario},title = {See the Difference: Direct Pre-Image Reconstruction and Pose Estimation by Differentiating HOG},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | The Histogram of Oriented Gradient (HOG) descriptor has led to many advances in computer vision over the last decade and is still part of many state of the art approaches. We realize that the associated feature computation is piecewise differentiable and therefore many pipelines which build on HOG can be made different... | [
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53 | An Efficient Statistical Method for Image Noise Level Estimation | [
"Guangyong Chen",
"Fengyuan Zhu",
"Pheng Ann Heng"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Chen_An_Efficient_Statistical_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Chen_An_Efficient_Statistical_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Chen_2015_ICCV,author = {Chen, Guangyong and Zhu, Fengyuan and Heng, Pheng Ann},title = {An Efficient Statistical Method for Image Noise Level Estimation},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | In this paper, we address the problem of estimating noise level from a single image contaminated by additive zero-mean Gaussian noise. We first provide rigorous analysis on the statistical relationship between the noise variance and the eigenvalues of the covariance matrix of patches within an image, which shows that m... | [
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54 | Contour Detection and Characterization for Asynchronous Event Sensors | [
"Francisco Barranco",
"Ching L. Teo",
"Cornelia Fermuller",
"Yiannis Aloimonos"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Barranco_Contour_Detection_and_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Barranco_Contour_Detection_and_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Barranco_2015_ICCV,author = {Barranco, Francisco and Teo, Ching L. and Fermuller, Cornelia and Aloimonos, Yiannis},title = {Contour Detection and Characterization for Asynchronous Event Sensors},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},ye... | The bio-inspired, asynchronous event-based dynamic vision sensor records temporal changes in the luminance of the scene at high temporal resolution. Since events are only triggered at significant luminance changes, most events occur at the boundary of objects and their parts. The detection of these contours is an essen... | [
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55 | Class-Specific Image Deblurring | [
"Saeed Anwar",
"Cong Phuoc Huynh",
"Fatih Porikli"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Anwar_Class-Specific_Image_Deblurring_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Anwar_Class-Specific_Image_Deblurring_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Anwar_2015_ICCV,author = {Anwar, Saeed and Huynh, Cong Phuoc and Porikli, Fatih},title = {Class-Specific Image Deblurring},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | In image deblurring, a fundamental problem is that the blur kernel suppresses a number of spatial frequencies that are difficult to recover reliably. In this paper, we explore the potential of a class-specific image prior for recovering spatial frequencies attenuated by the blurring process. Specifically, we devise a p... | [
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56 | High-for-Low and Low-for-High: Efficient Boundary Detection From Deep Object Features and its Applications to High-Level Vision | [
"Gedas Bertasius",
"Jianbo Shi",
"Lorenzo Torresani"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Bertasius_High-for-Low_and_Low-for-High_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Bertasius_High-for-Low_and_Low-for-High_ICCV_2015_paper.pdf | null | 1504.06201 | title_snapshot | @InProceedings{Bertasius_2015_ICCV,author = {Bertasius, Gedas and Shi, Jianbo and Torresani, Lorenzo},title = {High-for-Low and Low-for-High: Efficient Boundary Detection From Deep Object Features and its Applications to High-Level Vision},booktitle = {Proceedings of the IEEE International Conference on Computer Vision... | Most of the current boundary detection systems rely exclusively on low-level features, such as color and texture. However, perception studies suggest that humans employ object-level reasoning when judging if a particular pixel is a boundary. Inspired by this observation, in this work we show how to predict boundaries b... | [
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57 | Variational Depth Superresolution Using Example-Based Edge Representations | [
"David Ferstl",
"Matthias Ruther",
"Horst Bischof"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Ferstl_Variational_Depth_Superresolution_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Ferstl_Variational_Depth_Superresolution_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Ferstl_2015_ICCV,author = {Ferstl, David and Ruther, Matthias and Bischof, Horst},title = {Variational Depth Superresolution Using Example-Based Edge Representations},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | In this paper we propose a novel method for depth image superresolution which combines recent advances in example based upsampling with variational superresolution based on a known blur kernel. Most traditional depth superresolution approaches try to use additional high resolution intensity images as guidance for super... | [
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58 | Conditioned Regression Models for Non-Blind Single Image Super-Resolution | [
"Gernot Riegler",
"Samuel Schulter",
"Matthias Ruther",
"Horst Bischof"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Riegler_Conditioned_Regression_Models_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Riegler_Conditioned_Regression_Models_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Riegler_2015_ICCV,author = {Riegler, Gernot and Schulter, Samuel and Ruther, Matthias and Bischof, Horst},title = {Conditioned Regression Models for Non-Blind Single Image Super-Resolution},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = ... | Single image super-resolution is an important task in the field of computer vision and finds many practical applications. Current state-of-the-art methods typically rely on machine learning algorithms to infer a mapping from low- to high-resolution images. These methods use a single fixed blur kernel during training ... | [
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59 | Video Super-Resolution via Deep Draft-Ensemble Learning | [
"Renjie Liao",
"Xin Tao",
"Ruiyu Li",
"Ziyang Ma",
"Jiaya Jia"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Liao_Video_Super-Resolution_via_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Liao_Video_Super-Resolution_via_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Liao_2015_ICCV,author = {Liao, Renjie and Tao, Xin and Li, Ruiyu and Ma, Ziyang and Jia, Jiaya},title = {Video Super-Resolution via Deep Draft-Ensemble Learning},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | We propose a new direction for fast video super-resolution (VideoSR) via a SR draft ensemble, which is defined as the set of high-resolution patch candidates before final image deconvolution. Our method contains two main components -- i.e., SR draft ensemble generation and its optimal reconstruction. The first componen... | [
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60 | Pan-Sharpening With a Hyper-Laplacian Penalty | [
"Yiyong Jiang",
"Xinghao Ding",
"Delu Zeng",
"Yue Huang",
"John Paisley"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Jiang_Pan-Sharpening_With_a_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Jiang_Pan-Sharpening_With_a_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Jiang_2015_ICCV,author = {Jiang, Yiyong and Ding, Xinghao and Zeng, Delu and Huang, Yue and Paisley, John},title = {Pan-Sharpening With a Hyper-Laplacian Penalty},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | Pan-sharpening is the task of fusing spectral information in low resolution multispectral images with spatial information in a corresponding high resolution panchromatic image. In such approaches, there is a trade-off between spectral and spatial quality, as well as computational efficiency. We present a method for pan... | [
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61 | Video Restoration Against Yin-Yang Phasing | [
"Xiaolin Wu",
"Zhenhao Li",
"Xiaowei Deng"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Wu_Video_Restoration_Against_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Wu_Video_Restoration_Against_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Wu_2015_ICCV,author = {Wu, Xiaolin and Li, Zhenhao and Deng, Xiaowei},title = {Video Restoration Against Yin-Yang Phasing},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | A common video degradation problem, which is largely untreated in literature, is what we call Yin-Yang Phasing (YYP). YYP is characterized by involuntary, dramatic flip-flop in the intensity and possibly chromaticity of an object as the video plays. Such temporal artifacts occur under ill illumination conditions and ... | [
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62 | Rolling Shutter Super-Resolution | [
"Abhijith Punnappurath",
"Vijay Rengarajan",
"A.N. Rajagopalan"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Punnappurath_Rolling_Shutter_Super-Resolution_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Punnappurath_Rolling_Shutter_Super-Resolution_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Punnappurath_2015_ICCV,author = {Punnappurath, Abhijith and Rengarajan, Vijay and Rajagopalan, A.N.},title = {Rolling Shutter Super-Resolution},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | Classical multi-image super-resolution (SR) algorithms, designed for CCD cameras, assume that the motion among the images is global. But CMOS sensors that have increasingly started to replace their more expensive CCD counterparts in many applications do not respect this assumption if there is a motion of the camera rel... | [
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63 | Learning Large-Scale Automatic Image Colorization | [
"Aditya Deshpande",
"Jason Rock",
"David Forsyth"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Deshpande_Learning_Large-Scale_Automatic_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Deshpande_Learning_Large-Scale_Automatic_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Deshpande_2015_ICCV,author = {Deshpande, Aditya and Rock, Jason and Forsyth, David},title = {Learning Large-Scale Automatic Image Colorization},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | We describe an automated method for image colorization that learns to colorize from examples. Our method exploits a LEARCH framework to train a quadratic objective function in the chromaticity maps, comparable to a Gaussian random field. The coefficients of the objective function are conditioned on image features, us... | [
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64 | Compression Artifacts Reduction by a Deep Convolutional Network | [
"Chao Dong",
"Yubin Deng",
"Chen Change Loy",
"Xiaoou Tang"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Dong_Compression_Artifacts_Reduction_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Dong_Compression_Artifacts_Reduction_ICCV_2015_paper.pdf | null | 1504.06993 | title_snapshot | @InProceedings{Dong_2015_ICCV,author = {Dong, Chao and Deng, Yubin and Loy, Chen Change and Tang, Xiaoou},title = {Compression Artifacts Reduction by a Deep Convolutional Network},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | Lossy compression introduces complex compression artifacts, particularly the blocking artifacts, ringing effects and blurring. Existing algorithms either focus on removing blocking artifacts and produce blurred output, or restores sharpened images that are accompanied with ringing effects. Inspired by the deep convolut... | [
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65 | Multiple-Hypothesis Affine Region Estimation With Anisotropic LoG Filters | [
"Takahiro Hasegawa",
"Mitsuru Ambai",
"Kohta Ishikawa",
"Gou Koutaki",
"Yuji Yamauchi",
"Takayoshi Yamashita",
"Hironobu Fujiyoshi"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Hasegawa_Multiple-Hypothesis_Affine_Region_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Hasegawa_Multiple-Hypothesis_Affine_Region_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Hasegawa_2015_ICCV,author = {Hasegawa, Takahiro and Ambai, Mitsuru and Ishikawa, Kohta and Koutaki, Gou and Yamauchi, Yuji and Yamashita, Takayoshi and Fujiyoshi, Hironobu},title = {Multiple-Hypothesis Affine Region Estimation With Anisotropic LoG Filters},booktitle = {Proceedings of the IEEE Internation... | We propose a method for estimating multiple-hypothesis affine regions from a keypoint by using an anisotropic Laplacian-of-Gaussian (LoG) filter. Although conventional affine region detectors, such as Hessian/Harris-Affine, iterate to find an affine region that fits a given image patch, such iterative searching is adve... | [
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66 | A Self-Paced Multiple-Instance Learning Framework for Co-Saliency Detection | [
"Dingwen Zhang",
"Deyu Meng",
"Chao Li",
"Lu Jiang",
"Qian Zhao",
"Junwei Han"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Zhang_A_Self-Paced_Multiple-Instance_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Zhang_A_Self-Paced_Multiple-Instance_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Zhang_2015_ICCV,author = {Zhang, Dingwen and Meng, Deyu and Li, Chao and Jiang, Lu and Zhao, Qian and Han, Junwei},title = {A Self-Paced Multiple-Instance Learning Framework for Co-Saliency Detection},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {Decemb... | As an interesting and emerging topic, co-saliency detection aims at simultaneously extracting common salient objects in a group of images. Traditional co-saliency detection approaches rely heavily on human knowledge for designing hand-crafted metrics to explore the intrinsic patterns underlying co-salient objects. Such... | [
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67 | External Patch Prior Guided Internal Clustering for Image Denoising | [
"Fei Chen",
"Lei Zhang",
"Huimin Yu"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Chen_External_Patch_Prior_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Chen_External_Patch_Prior_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Chen_2015_ICCV,author = {Chen, Fei and Zhang, Lei and Yu, Huimin},title = {External Patch Prior Guided Internal Clustering for Image Denoising},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | Natural image modeling plays a key role in many vision problems such as image denoising. Image priors are widely used to regularize the denoising process, which is an illposed inverse problem. One category of denoising methods exploit the priors (e.g., TV, sparsity) learned from external clean images to reconstruct the... | [
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68 | Self-Calibration of Optical Lenses | [
"Michael Hirsch",
"Bernhard Scholkopf"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Hirsch_Self-Calibration_of_Optical_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Hirsch_Self-Calibration_of_Optical_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Hirsch_2015_ICCV,author = {Hirsch, Michael and Scholkopf, Bernhard},title = {Self-Calibration of Optical Lenses},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | Even high-quality lenses suffer from optical aberrations, especially when used at full aperture. Furthermore, there are significant lens-to-lens deviations due to manufacturing tolerances, often rendering current software solutions like DxO, Lightroom, and PTLens insufficient as they don't adapt and only include generi... | [
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69 | Illumination Robust Color Naming via Label Propagation | [
"Yuanliu liu",
"Zejian Yuan",
"Badong Chen",
"Jianru Xue",
"Nanning Zheng"
] | https://openaccess.thecvf.com/content_iccv_2015/html/liu_Illumination_Robust_Color_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/liu_Illumination_Robust_Color_ICCV_2015_paper.pdf | null | null | null | @InProceedings{liu_2015_ICCV,author = {liu, Yuanliu and Yuan, Zejian and Chen, Badong and Xue, Jianru and Zheng, Nanning},title = {Illumination Robust Color Naming via Label Propagation},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | Color composition is an important property for many computer vision tasks like image retrieval and object classification. In this paper we address the problem of inferring the color composition of the intrinsic reflectance of objects, where the shadows and highlights may change the observed color dramatically. We achie... | [
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70 | Unsupervised Cross-Modal Synthesis of Subject-Specific Scans | [
"Raviteja Vemulapalli",
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"Shaohua Kevin Zhou"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Vemulapalli_Unsupervised_Cross-Modal_Synthesis_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Vemulapalli_Unsupervised_Cross-Modal_Synthesis_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Vemulapalli_2015_ICCV,author = {Vemulapalli, Raviteja and Van Nguyen, Hien and Zhou, Shaohua Kevin},title = {Unsupervised Cross-Modal Synthesis of Subject-Specific Scans},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | Recently, cross-modal synthesis of subject-specific scans has been receiving significant attention from the medical imaging community. Though various synthesis approaches have been introduced in the recent past, most of them are either tailored to a specific application or proposed for the supervised setting, i.e., the... | [
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71 | Learning to Boost Filamentary Structure Segmentation | [
"Lin Gu",
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] | https://openaccess.thecvf.com/content_iccv_2015/html/Gu_Learning_to_Boost_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Gu_Learning_to_Boost_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Gu_2015_ICCV,author = {Gu, Lin and Cheng, Li},title = {Learning to Boost Filamentary Structure Segmentation},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | The challenging problem of filamentary structure segmentation has a broad range of applications in biological and medical fields. A critical yet challenging issue remains on how to detect and restore the small filamentary fragments from backgrounds: The small fragments are of diverse shapes and appearances, meanwhile t... | [
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72 | Weakly-Supervised Structured Output Learning With Flexible and Latent Graphs Using High-Order Loss Functions | [
"Gustavo Carneiro",
"Tingying Peng",
"Christine Bayer",
"Nassir Navab"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Carneiro_Weakly-Supervised_Structured_Output_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Carneiro_Weakly-Supervised_Structured_Output_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Carneiro_2015_ICCV,author = {Carneiro, Gustavo and Peng, Tingying and Bayer, Christine and Navab, Nassir},title = {Weakly-Supervised Structured Output Learning With Flexible and Latent Graphs Using High-Order Loss Functions},booktitle = {Proceedings of the IEEE International Conference on Computer Vision... | We introduce two new structured output models that use a latent graph, which is flexible in terms of the number of nodes and structure, where the training process minimises a high-order loss function using a weakly annotated training set. These models are developed in the context of microscopy imaging of malignant tumo... | [
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73 | Efficient Classifier Training to Minimize False Merges in Electron Microscopy Segmentation | [
"Toufiq Parag",
"Dan C. Ciresan",
"Alessandro Giusti"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Parag_Efficient_Classifier_Training_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Parag_Efficient_Classifier_Training_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Parag_2015_ICCV,author = {Parag, Toufiq and Ciresan, Dan C. and Giusti, Alessandro},title = {Efficient Classifier Training to Minimize False Merges in Electron Microscopy Segmentation},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015... | The prospect of neural reconstruction from Electron Microscopy (EM) images has been elucidated by the automatic segmentation algorithms. Although segmentation algorithms eliminate the necessity of tracing the neurons by hand, significant manual effort is still essential for correcting the mistakes they make. A consider... | [
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74 | On Statistical Analysis of Neuroimages With Imperfect Registration | [
"Won Hwa Kim",
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"Sterling C. Johnson",
"Ozioma C. Okonkwo",
"Vikas Singh"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Kim_On_Statistical_Analysis_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Kim_On_Statistical_Analysis_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Kim_2015_ICCV,author = {Kim, Won Hwa and Ravi, Sathya N. and Johnson, Sterling C. and Okonkwo, Ozioma C. and Singh, Vikas},title = {On Statistical Analysis of Neuroimages With Imperfect Registration},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {Decembe... | A variety of studies in neuroscience/neuroimaging seek to perform statistical inference on the acquired brain image scans for diagnosis as well as understanding the pathological manifestation of diseases. To do so, an important first step is to register (or co-register) all of the image data into a common coordinate sy... | [
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75 | Convex Optimization With Abstract Linear Operators | [
"Steven Diamond",
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] | https://openaccess.thecvf.com/content_iccv_2015/html/Diamond_Convex_Optimization_With_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Diamond_Convex_Optimization_With_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Diamond_2015_ICCV,author = {Diamond, Steven and Boyd, Stephen},title = {Convex Optimization With Abstract Linear Operators},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | We introduce a convex optimization modeling framework that transforms a convex optimization problem expressed in a form natural and convenient for the user into an equivalent cone program in a way that preserves fast linear transforms in the original problem. By representing linear functions in the transformation proce... | [
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76 | Building Dynamic Cloud Maps From the Ground Up | [
"Calvin Murdock",
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"Robert Pless"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Murdock_Building_Dynamic_Cloud_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Murdock_Building_Dynamic_Cloud_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Murdock_2015_ICCV,author = {Murdock, Calvin and Jacobs, Nathan and Pless, Robert},title = {Building Dynamic Cloud Maps From the Ground Up},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | Satellite imagery of cloud cover is extremely important for understanding and predicting weather. We demonstrate how this imagery can be constructed "from the ground up" without requiring expensive geo-stationary satellites. This is accomplished through a novel approach to approximate continental-scale cloud maps using... | [
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77 | A Versatile Learning-Based 3D Temporal Tracker: Scalable, Robust, Online | [
"David Joseph Tan",
"Federico Tombari",
"Slobodan Ilic",
"Nassir Navab"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Tan_A_Versatile_Learning-Based_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Tan_A_Versatile_Learning-Based_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Tan_2015_ICCV,author = {Tan, David Joseph and Tombari, Federico and Ilic, Slobodan and Navab, Nassir},title = {A Versatile Learning-Based 3D Temporal Tracker: Scalable, Robust, Online},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015... | This paper proposes a temporal tracking algorithm based on Random Forest that uses depth images to estimate and track the 3D pose of a rigid object in real-time. Compared to the state of the art aimed at the same goal, our algorithm holds important attributes such as high robustness against holes and occlusion, low com... | [
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78 | Realtime Edge-Based Visual Odometry for a Monocular Camera | [
"Juan Jose Tarrio",
"Sol Pedre"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Tarrio_Realtime_Edge-Based_Visual_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Tarrio_Realtime_Edge-Based_Visual_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Tarrio_2015_ICCV,author = {Tarrio, Juan Jose and Pedre, Sol},title = {Realtime Edge-Based Visual Odometry for a Monocular Camera},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | In this work we present a novel algorithm for realtime visual odometry for a monocular camera. The main idea is to develop an approach between classical feature-based visual odometry systems and modern direct dense/semi-dense methods, trying to benefit from the best attributes of both. Similar to feature-based systems,... | [
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79 | Fill and Transfer: A Simple Physics-Based Approach for Containability Reasoning | [
"Lap-Fai Yu",
"Noah Duncan",
"Sai-Kit Yeung"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Yu_Fill_and_Transfer_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Yu_Fill_and_Transfer_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Yu_2015_ICCV,author = {Yu, Lap-Fai and Duncan, Noah and Yeung, Sai-Kit},title = {Fill and Transfer: A Simple Physics-Based Approach for Containability Reasoning},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | The visual perception of object affordances has emerged as a useful ingredient for building powerful computer vision and robotic applications. In this paper we introduce a novel approach to reason about liquid containability - the affordance of containing liquid. Our approach analyzes container objects based on two sim... | [
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80 | On Linear Structure From Motion for Light Field Cameras | [
"Ole Johannsen",
"Antonin Sulc",
"Bastian Goldluecke"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Johannsen_On_Linear_Structure_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Johannsen_On_Linear_Structure_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Johannsen_2015_ICCV,author = {Johannsen, Ole and Sulc, Antonin and Goldluecke, Bastian},title = {On Linear Structure From Motion for Light Field Cameras},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | We present a novel approach to relative pose estimation which is tailored to 4D light field cameras. From the relationships between scene geometry and light field structure and an analysis of the light field projection in terms of Pluecker ray coordinates, we deduce a set of linear constraints on ray space corresponden... | [
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81 | 3D Object Reconstruction From Hand-Object Interactions | [
"Dimitrios Tzionas",
"Juergen Gall"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Tzionas_3D_Object_Reconstruction_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Tzionas_3D_Object_Reconstruction_ICCV_2015_paper.pdf | null | 1704.00529 | title_snapshot | @InProceedings{Tzionas_2015_ICCV,author = {Tzionas, Dimitrios and Gall, Juergen},title = {3D Object Reconstruction From Hand-Object Interactions},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | Recent advances have enabled 3d object reconstruction approaches using a single off-the-shelf RGB-D camera. Although these approaches are successful for a wide range of object classes, they rely on stable and distinctive geometric or texture features. Many objects like mechanical parts, toys, household or decorative ar... | [
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82 | Minimal Solvers for 3D Geometry From Satellite Imagery | [
"Enliang Zheng",
"Ke Wang",
"Enrique Dunn",
"Jan-Michael Frahm"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Zheng_Minimal_Solvers_for_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Zheng_Minimal_Solvers_for_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Zheng_2015_ICCV,author = {Zheng, Enliang and Wang, Ke and Dunn, Enrique and Frahm, Jan-Michael},title = {Minimal Solvers for 3D Geometry From Satellite Imagery},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | We propose two novel minimal solvers which advance the state of the art in satellite imagery processing. Our methods are efficient and do not rely on the prior existence of complex inverse mapping functions to correlate 2D image coordinates and 3D terrain. Our first solver improves on the stereo correspondence problem ... | [
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83 | An Efficient Minimal Solution for Multi-Camera Motion | [
"Jonathan Ventura",
"Clemens Arth",
"Vincent Lepetit"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Ventura_An_Efficient_Minimal_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Ventura_An_Efficient_Minimal_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Ventura_2015_ICCV,author = {Ventura, Jonathan and Arth, Clemens and Lepetit, Vincent},title = {An Efficient Minimal Solution for Multi-Camera Motion},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | We propose an efficient method for estimating the motion of a multi-camera rig from a minimal set of feature correspondences. Existing methods for solving the multi-camera relative pose problem require extra correspondences, are slow to compute, and/or produce a multitude of solutions. Our solution uses a first-order... | [
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84 | Learning Shape, Motion and Elastic Models in Force Space | [
"Antonio Agudo",
"Francesc Moreno-Noguer"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Agudo_Learning_Shape_Motion_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Agudo_Learning_Shape_Motion_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Agudo_2015_ICCV,author = {Agudo, Antonio and Moreno-Noguer, Francesc},title = {Learning Shape, Motion and Elastic Models in Force Space},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | In this paper, we address the problem of simultaneously recovering the 3D shape and pose of a deformable and potentially elastic object from 2D motion. This is a highly ambiguous problem typically tackled by using low-rank shape and trajectory constraints. We show that formulating the problem in terms of a low-rank f... | [
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85 | A Versatile Scene Model With Differentiable Visibility Applied to Generative Pose Estimation | [
"Helge Rhodin",
"Nadia Robertini",
"Christian Richardt",
"Hans-Peter Seidel",
"Christian Theobalt"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Rhodin_A_Versatile_Scene_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Rhodin_A_Versatile_Scene_ICCV_2015_paper.pdf | null | 1602.03725 | title_snapshot | @InProceedings{Rhodin_2015_ICCV,author = {Rhodin, Helge and Robertini, Nadia and Richardt, Christian and Seidel, Hans-Peter and Theobalt, Christian},title = {A Versatile Scene Model With Differentiable Visibility Applied to Generative Pose Estimation},booktitle = {Proceedings of the IEEE International Conference on Com... | Generative reconstruction methods compute the 3D configuration (such as pose and/or geometry) of a shape by optimizing the overlap of the projected 3D shape model with images. Proper handling of occlusions is a big challenge, since the visibility function that indicates if a surface point is seen from a camera can ofte... | [
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86 | Semantic Pose Using Deep Networks Trained on Synthetic RGB-D | [
"Jeremie Papon",
"Markus Schoeler"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Papon_Semantic_Pose_Using_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Papon_Semantic_Pose_Using_ICCV_2015_paper.pdf | null | 1508.00835 | title_snapshot | @InProceedings{Papon_2015_ICCV,author = {Papon, Jeremie and Schoeler, Markus},title = {Semantic Pose Using Deep Networks Trained on Synthetic RGB-D},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | In this work we address the problem of indoor scene understanding from RGB-D images. Specifically, we propose to find instances of common furniture classes, their spatial extent, and their pose with respect to generalized class models. To accomplish this, we use a deep, wide, multi-output convolutional neural network (... | [
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87 | Exploiting High Level Scene Cues in Stereo Reconstruction | [
"Simon Hadfield",
"Richard Bowden"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Hadfield_Exploiting_High_Level_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Hadfield_Exploiting_High_Level_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Hadfield_2015_ICCV,author = {Hadfield, Simon and Bowden, Richard},title = {Exploiting High Level Scene Cues in Stereo Reconstruction},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | We present a novel approach to 3D reconstruction which is inspired by the human visual system. This system unifies standard appearance matching and triangulation techniques with higher level reasoning and scene understanding, in order to resolve ambiguities between different interpretations of the scene. The types of r... | [
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88 | Point Triangulation Through Polyhedron Collapse Using the l[?] Norm | [
"Simon Donne",
"Bart Goossens",
"Wilfried Philips"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Donne_Point_Triangulation_Through_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Donne_Point_Triangulation_Through_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Donne_2015_ICCV,author = {Donne, Simon and Goossens, Bart and Philips, Wilfried},title = {Point Triangulation Through Polyhedron Collapse Using the l[?] Norm},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | Multi-camera triangulation of feature points based on a minimisation of the overall L2 reprojection error can get stuck in suboptimal local minima or require slow global optimisation. For this reason, researchers have proposed optimising the L-infinity norm of the L2 single view reprojection errors, which avoids the pr... | [
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89 | Optimizing the Viewing Graph for Structure-From-Motion | [
"Chris Sweeney",
"Torsten Sattler",
"Tobias Hollerer",
"Matthew Turk",
"Marc Pollefeys"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Sweeney_Optimizing_the_Viewing_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Sweeney_Optimizing_the_Viewing_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Sweeney_2015_ICCV,author = {Sweeney, Chris and Sattler, Torsten and Hollerer, Tobias and Turk, Matthew and Pollefeys, Marc},title = {Optimizing the Viewing Graph for Structure-From-Motion},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {... | The viewing graph represents a set of views that are related by pairwise relative geometries. In the context of Structure-from-Motion (SfM), the viewing graph is the input to the incremental or global estimation pipeline. Much effort has been put towards developing robust algorithms to overcome potentially inaccurate r... | [
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90 | Intrinsic Scene Decomposition From RGB-D images | [
"Mohammed Hachama",
"Bernard Ghanem",
"Peter Wonka"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Hachama_Intrinsic_Scene_Decomposition_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Hachama_Intrinsic_Scene_Decomposition_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Hachama_2015_ICCV,author = {Hachama, Mohammed and Ghanem, Bernard and Wonka, Peter},title = {Intrinsic Scene Decomposition From RGB-D images},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | In this paper, we address the problem of computing an intrinsic decomposition of the colors of a surface into an albedo and a shading term. The surface is reconstructed from a single or multiple RGB-D images of a static scene obtained from different views. We thereby extend and improve existing works in the area of int... | [
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91 | 3D Hand Pose Estimation Using Randomized Decision Forest With Segmentation Index Points | [
"Peiyi Li",
"Haibin Ling",
"Xi Li",
"Chunyuan Liao"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Li_3D_Hand_Pose_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Li_3D_Hand_Pose_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Li_2015_ICCV,author = {Li, Peiyi and Ling, Haibin and Li, Xi and Liao, Chunyuan},title = {3D Hand Pose Estimation Using Randomized Decision Forest With Segmentation Index Points},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | In this paper, we propose a real-time 3D hand pose estimation algorithm using the randomized decision forest framework. Our algorithm takes a depth image as input and generates a set of skeletal joints as output. Previous decision forest-based methods often give labels to all points in a point cloud at a very early sta... | [
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92 | Accurate Camera Calibration Robust to Defocus Using a Smartphone | [
"Hyowon Ha",
"Yunsu Bok",
"Kyungdon Joo",
"Jiyoung Jung",
"In So Kweon"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Ha_Accurate_Camera_Calibration_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Ha_Accurate_Camera_Calibration_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Ha_2015_ICCV,author = {Ha, Hyowon and Bok, Yunsu and Joo, Kyungdon and Jung, Jiyoung and Kweon, In So},title = {Accurate Camera Calibration Robust to Defocus Using a Smartphone},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | We propose a novel camera calibration method for defocused images using a smartphone under the assumption that the defocus blur is modeled as a convolution of a sharp image with a Gaussian point spread function (PSF). In contrast to existing calibration approaches which require well-focused images, the proposed method ... | [
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93 | High Quality Structure From Small Motion for Rolling Shutter Cameras | [
"Sunghoon Im",
"Hyowon Ha",
"Gyeongmin Choe",
"Hae-Gon Jeon",
"Kyungdon Joo",
"In So Kweon"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Im_High_Quality_Structure_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Im_High_Quality_Structure_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Im_2015_ICCV,author = {Im, Sunghoon and Ha, Hyowon and Choe, Gyeongmin and Jeon, Hae-Gon and Joo, Kyungdon and Kweon, In So},title = {High Quality Structure From Small Motion for Rolling Shutter Cameras},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {Dec... | We present a practical 3D reconstruction method to obtain a high-quality dense depth map from narrow-baseline image sequences captured by commercial digital cameras, such as DSLRs or mobile phones. Depth estimation from small motion has gained interest as a means of various photographic editing, but important limitatio... | [
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94 | Photogeometric Scene Flow for High-Detail Dynamic 3D Reconstruction | [
"Paulo F. U. Gotardo",
"Tomas Simon",
"Yaser Sheikh",
"Iain Matthews"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Gotardo_Photogeometric_Scene_Flow_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Gotardo_Photogeometric_Scene_Flow_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Gotardo_2015_ICCV,author = {Gotardo, Paulo F. U. and Simon, Tomas and Sheikh, Yaser and Matthews, Iain},title = {Photogeometric Scene Flow for High-Detail Dynamic 3D Reconstruction},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | Photometric stereo (PS) is an established technique for high-detail reconstruction of 3D geometry and appearance. To correct for surface integration errors, PS is often combined with multiview stereo (MVS). With dynamic objects, PS reconstruction also faces the problem of computing optical flow (OF) for image alignment... | [
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95 | Blur-Aware Disparity Estimation From Defocus Stereo Images | [
"Ching-Hui Chen",
"Hui Zhou",
"Timo Ahonen"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Chen_Blur-Aware_Disparity_Estimation_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Chen_Blur-Aware_Disparity_Estimation_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Chen_2015_ICCV,author = {Chen, Ching-Hui and Zhou, Hui and Ahonen, Timo},title = {Blur-Aware Disparity Estimation From Defocus Stereo Images},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | Defocus blur usually causes performance degradation in establishing the visual correspondence between stereo images. We propose a blur-aware disparity estimation method that is robust to the mismatch of focus in stereo images. The relative blur resulting from the mismatch of focus between stereo images is approximated ... | [
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96 | Global Structure-From-Motion by Similarity Averaging | [
"Zhaopeng Cui",
"Ping Tan"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Cui_Global_Structure-From-Motion_by_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Cui_Global_Structure-From-Motion_by_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Cui_2015_ICCV,author = {Cui, Zhaopeng and Tan, Ping},title = {Global Structure-From-Motion by Similarity Averaging},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | Global structure-from-motion (SfM) methods solve all cameras simultaneously from all available relative motions. It has better potential in both reconstruction accuracy and computation efficiency than incremental methods. However, global SfM is challenging, mainly because of two reasons. Firstly, translation averaging ... | [
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97 | Massively Parallel Multiview Stereopsis by Surface Normal Diffusion | [
"Silvano Galliani",
"Katrin Lasinger",
"Konrad Schindler"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Galliani_Massively_Parallel_Multiview_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Galliani_Massively_Parallel_Multiview_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Galliani_2015_ICCV,author = {Galliani, Silvano and Lasinger, Katrin and Schindler, Konrad},title = {Massively Parallel Multiview Stereopsis by Surface Normal Diffusion},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | We present a new, massively parallel method for high-quality multiview matching. Our work builds on the Patchmatch idea: starting from randomly generated 3D planes in scene space, the best-fitting planes are iteratively propagated and refined to obtain a 3D depth and normal field per view, such that a robust photo-cons... | [
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98 | Variational PatchMatch MultiView Reconstruction and Refinement | [
"Philipp Heise",
"Brian Jensen",
"Sebastian Klose",
"Alois Knoll"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Heise_Variational_PatchMatch_MultiView_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Heise_Variational_PatchMatch_MultiView_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Heise_2015_ICCV,author = {Heise, Philipp and Jensen, Brian and Klose, Sebastian and Knoll, Alois},title = {Variational PatchMatch MultiView Reconstruction and Refinement},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | In this work we propose a novel approach to the problem of multi-view stereo reconstruction. Building upon the previously proposed PatchMatch stereo and PM-Huber algorithm we introduce an extension to the multi-view scenario that employs an iterative refinement scheme. Our proposed approach uses an extended and robusti... | [
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99 | As-Rigid-As-Possible Volumetric Shape-From-Template | [
"Shaifali Parashar",
"Daniel Pizarro",
"Adrien Bartoli",
"Toby Collins"
] | https://openaccess.thecvf.com/content_iccv_2015/html/Parashar_As-Rigid-As-Possible_Volumetric_Shape-From-Template_ICCV_2015_paper.html | https://openaccess.thecvf.com/content_iccv_2015/papers/Parashar_As-Rigid-As-Possible_Volumetric_Shape-From-Template_ICCV_2015_paper.pdf | null | null | null | @InProceedings{Parashar_2015_ICCV,author = {Parashar, Shaifali and Pizarro, Daniel and Bartoli, Adrien and Collins, Toby},title = {As-Rigid-As-Possible Volumetric Shape-From-Template},booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},month = {December},year = {2015}} | The objective of Shape-from-Template (SfT) is to infer an object's shape from a single image and a 3D object tem- plate. Existing methods are called thin-shell SfT as they represent the object by its outer surface. This may be an open surface for thin objects such as a piece of paper or a closed surface for thicker obj... | [
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... |
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