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0 | Fast and Accurate Image Matching with Cascade Hashing for 3D Reconstruction | [
"Jian Cheng",
"Cong Leng",
"Jiaxiang Wu",
"Hainan Cui",
"Hanqing Lu"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Cheng_Fast_and_Accurate_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Cheng_Fast_and_Accurate_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Cheng_2014_CVPR,author = {Cheng, Jian and Leng, Cong and Wu, Jiaxiang and Cui, Hainan and Lu, Hanqing},title = {Fast and Accurate Image Matching with Cascade Hashing for 3D Reconstruction},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},ye... | Image matching is one of the most challenging stages in 3D reconstruction, which usually occupies half of computational cost and inaccurate matching may lead to failure of reconstruction. Therefore, fast and accurate image matching is very crucial for 3D reconstruction. In this paper, we proposed a Cascade Hashing stra... | [
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1 | Predicting Matchability | [
"Wilfried Hartmann",
"Michal Havlena",
"Konrad Schindler"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Hartmann_Predicting_Matchability_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Hartmann_Predicting_Matchability_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Hartmann_2014_CVPR,author = {Hartmann, Wilfried and Havlena, Michal and Schindler, Konrad},title = {Predicting Matchability},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | The initial steps of many computer vision algorithms are interest point extraction and matching. In larger image sets the pairwise matching of interest point descriptors between images is an important bottleneck. For each descriptor in one image the (approximate) nearest neighbor in the other one has to be found and ch... | [
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2 | Trinocular Geometry Revisited | [
"Jean Ponce",
"Martial Hebert"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Ponce_Trinocular_Geometry_Revisited_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Ponce_Trinocular_Geometry_Revisited_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Ponce_2014_CVPR,author = {Ponce, Jean and Hebert, Martial},title = {Trinocular Geometry Revisited},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | When do the visual rays associated with triplets of point correspondences converge, that is, intersect in a common point? Classical models of trinocular geometry based on the fundamental matrices and trifocal tensor associated with the corresponding cameras only provide partial answers to this fundamental question, in ... | [
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3 | Critical Configurations For Radial Distortion Self-Calibration | [
"Changchang Wu"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Wu_Critical_Configurations_For_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Wu_Critical_Configurations_For_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Wu_2014_CVPR,author = {Wu, Changchang},title = {Critical Configurations For Radial Distortion Self-Calibration},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | In this paper, we study the configurations of motion and structure that lead to inherent ambiguities in radial distortion estimation (or 3D reconstruction with unknown radial distortions). By analyzing the motion field of radially distorted images, we solve for critical surface pairs that can lead to the same motion f... | [
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4 | Minimal Solvers for Relative Pose with a Single Unknown Radial Distortion | [
"Yubin Kuang",
"Jan E. Solem",
"Fredrik Kahl",
"Kalle Astrom"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Kuang_Minimal_Solvers_for_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Kuang_Minimal_Solvers_for_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Kuang_2014_CVPR,author = {Kuang, Yubin and Solem, Jan E. and Kahl, Fredrik and Astrom, Kalle},title = {Minimal Solvers for Relative Pose with a Single Unknown Radial Distortion},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}... | In this paper, we study the problems of estimating relative pose between two cameras in the presence of radial distortion. Specifically, we consider minimal problems where one of the cameras has no or known radial distortion. There are three useful cases for this setup with a single unknown distortion: (i) fundamenta... | [
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5 | Reconstructing PASCAL VOC | [
"Sara Vicente",
"Joao Carreira",
"Lourdes Agapito",
"Jorge Batista"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Vicente_Reconstructing_PASCAL_VOC_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Vicente_Reconstructing_PASCAL_VOC_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Vicente_2014_CVPR,author = {Vicente, Sara and Carreira, Joao and Agapito, Lourdes and Batista, Jorge},title = {Reconstructing PASCAL VOC},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | We address the problem of populating object category detection datasets with dense, per-object 3D reconstructions, bootstrapped from class labels, ground truth figure-ground segmentations and a small set of keypoint annotations. Our proposed algorithm first estimates camera viewpoint using rigid structure-from-motion, ... | [
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6 | Spectral Graph Reduction for Efficient Image and Streaming Video Segmentation | [
"Fabio Galasso",
"Margret Keuper",
"Thomas Brox",
"Bernt Schiele"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Galasso_Spectral_Graph_Reduction_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Galasso_Spectral_Graph_Reduction_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Galasso_2014_CVPR,author = {Galasso, Fabio and Keuper, Margret and Brox, Thomas and Schiele, Bernt},title = {Spectral Graph Reduction for Efficient Image and Streaming Video Segmentation},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},yea... | Computational and memory costs restrict spectral techniques to rather small graphs, which is a serious limitation especially in video segmentation. In this paper, we propose the use of a reduced graph based on superpixels. In contrast to previous work, the reduced graph is reweighted such that the resulting segmentatio... | [
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7 | Weakly Supervised Multiclass Video Segmentation | [
"Xiao Liu",
"Dacheng Tao",
"Mingli Song",
"Ying Ruan",
"Chun Chen",
"Jiajun Bu"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Liu_Weakly_Supervised_Multiclass_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Liu_Weakly_Supervised_Multiclass_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Liu_2014_CVPR,author = {Liu, Xiao and Tao, Dacheng and Song, Mingli and Ruan, Ying and Chen, Chun and Bu, Jiajun},title = {Weakly Supervised Multiclass Video Segmentation},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | The desire of enabling computers to learn semantic concepts from large quantities of Internet videos has motivated increasing interests on semantic video understanding, while video segmentation is important yet challenging for understanding videos. The main difficulty of video segmentation arises from the burden of lab... | [
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8 | Video Motion Segmentation Using New Adaptive Manifold Denoising Model | [
"Dijun Luo",
"Heng Huang"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Luo_Video_Motion_Segmentation_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Luo_Video_Motion_Segmentation_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Luo_2014_CVPR,author = {Luo, Dijun and Huang, Heng},title = {Video Motion Segmentation Using New Adaptive Manifold Denoising Model},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | Video motion segmentation techniques automatically segment and track objects and regions from videos or image sequences as a primary processing step for many computer vision applications. We propose a novel motion segmentation approach for both rigid and non-rigid objects using adaptive manifold denoising. We first in... | [
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9 | Cut, Glue & Cut: A Fast, Approximate Solver for Multicut Partitioning | [
"Thorsten Beier",
"Thorben Kroeger",
"Jorg H. Kappes",
"Ullrich Kothe",
"Fred A. Hamprecht"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Beier_Cut_Glue__2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Beier_Cut_Glue__2014_CVPR_paper.pdf | null | null | null | @InProceedings{Beier_2014_CVPR,author = {Beier, Thorsten and Kroeger, Thorben and Kappes, Jorg H. and Kothe, Ullrich and Hamprecht, Fred A.},title = {Cut, Glue & Cut: A Fast, Approximate Solver for Multicut Partitioning},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},... | Recently, unsupervised image segmentation has become increasingly popular. Starting from a superpixel segmentation, an edge-weighted region adjacency graph is constructed. Amongst all segmentations of the graph, the one which best conforms to the given image evidence, as measured by the sum of cut edge weights, is chos... | [
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10 | Neural Decision Forests for Semantic Image Labelling | [
"Samuel Rota Bulo",
"Peter Kontschieder"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Bulo_Neural_Decision_Forests_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Bulo_Neural_Decision_Forests_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Bulo_2014_CVPR,author = {Rota Bulo, Samuel and Kontschieder, Peter},title = {Neural Decision Forests for Semantic Image Labelling},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | In this work we present Neural Decision Forests, a novel approach to jointly tackle data representation- and discriminative learning within randomized decision trees. Recent advances of deep learning architectures demonstrate the power of embedding representation learning within the classifier – An idea that is intuiti... | [
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11 | Pulling Things out of Perspective | [
"Lubor Ladicky",
"Jianbo Shi",
"Marc Pollefeys"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Ladicky_Pulling_Things_out_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Ladicky_Pulling_Things_out_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Ladicky_2014_CVPR,author = {Ladicky, Lubor and Shi, Jianbo and Pollefeys, Marc},title = {Pulling Things out of Perspective},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | The limitations of current state-of-the-art methods for single-view depth estimation and semantic segmentations are closely tied to the property of perspective geometry, that the perceived size of the objects scales inversely with the distance. In this paper, we show that we can use this property to reduce the learnin... | [
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12 | Event Detection using Multi-Level Relevance Labels and Multiple Features | [
"Zhongwen Xu",
"Ivor W. Tsang",
"Yi Yang",
"Zhigang Ma",
"Alexander G. Hauptmann"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Xu_Event_Detection_using_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Xu_Event_Detection_using_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Xu_2014_CVPR,author = {Xu, Zhongwen and Tsang, Ivor W. and Yang, Yi and Ma, Zhigang and Hauptmann, Alexander G.},title = {Event Detection using Multi-Level Relevance Labels and Multiple Features},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {J... | We address the challenging problem of utilizing related exemplars for complex event detection while multiple features are available. Related exemplars share certain positive elements of the event, but have no uniform pattern due to the huge variance of relevance levels among different related exemplars. None of the exi... | [
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13 | Full-Angle Quaternions for Robustly Matching Vectors of 3D Rotations | [
"Stephan Liwicki",
"Minh-Tri Pham",
"Stefanos Zafeiriou",
"Maja Pantic",
"Bjorn Stenger"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Liwicki_Full-Angle_Quaternions_for_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Liwicki_Full-Angle_Quaternions_for_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Liwicki_2014_CVPR,author = {Liwicki, Stephan and Pham, Minh-Tri and Zafeiriou, Stefanos and Pantic, Maja and Stenger, Bjorn},title = {Full-Angle Quaternions for Robustly Matching Vectors of 3D Rotations},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},mo... | In this paper we introduce a new distance for robustly matching vectors of 3D rotations. A special representation of 3D rotations, which we coin full-angle quaternion (FAQ), allows us to express this distance as Euclidean. We apply the distance to the problems of 3D shape recognition from point clouds and 2D object tra... | [
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14 | Human vs. Computer in Scene and Object Recognition | [
"Ali Borji",
"Laurent Itti"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Borji_Human_vs._Computer_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Borji_Human_vs._Computer_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Borji_2014_CVPR,author = {Borji, Ali and Itti, Laurent},title = {Human vs. Computer in Scene and Object Recognition},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | Several decades of research in computer and primate vision have resulted in many models (some specialized for one problem, others more general) and invaluable experimental data. Here, to help focus research efforts onto the hardest unsolved problems, and bridge computer and human vision, we define a battery of 5 tests ... | [
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15 | Semi-supervised Spectral Clustering for Image Set Classification | [
"Arif Mahmood",
"Ajmal Mian",
"Robyn Owens"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Mahmood_Semi-supervised_Spectral_Clustering_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Mahmood_Semi-supervised_Spectral_Clustering_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Mahmood_2014_CVPR,author = {Mahmood, Arif and Mian, Ajmal and Owens, Robyn},title = {Semi-supervised Spectral Clustering for Image Set Classification},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | We present an image set classification algorithm based on unsupervised clustering of labeled training and unlabeled test data where labels are only used in the stopping criterion. The probability distribution of each class over the set of clusters is used to define a true set based similarity measure. To this end, we ... | [
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16 | Look at the Driver, Look at the Road: No Distraction! No Accident! | [
"Mahdi Rezaei",
"Reinhard Klette"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Rezaei_Look_at_the_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Rezaei_Look_at_the_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Rezaei_2014_CVPR,author = {Rezaei, Mahdi and Klette, Reinhard},title = {Look at the Driver, Look at the Road: No Distraction! No Accident!},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | The paper proposes an advanced driver-assistance system that correlates the driver's head pose to road hazards by analyzing both simultaneously. In particular, we aim at the prevention of rear-end crashes due to driver fatigue or distraction. We contribute by three novel ideas: Asymmetric appearance-modeling, 2D to 3D ... | [
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17 | Measuring Distance Between Unordered Sets of Different Sizes | [
"Andrew Gardner",
"Jinko Kanno",
"Christian A. Duncan",
"Rastko Selmic"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Gardner_Measuring_Distance_Between_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Gardner_Measuring_Distance_Between_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Gardner_2014_CVPR,author = {Gardner, Andrew and Kanno, Jinko and Duncan, Christian A. and Selmic, Rastko},title = {Measuring Distance Between Unordered Sets of Different Sizes},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | We present a distance metric based upon the notion of minimum-cost injective mappings between sets. Our function satisfies metric properties as long as the cost of the minimum mappings is derived from a semimetric, for which the triangle inequality is not necessarily satisfied. We show that the Jaccard distance (altern... | [
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18 | Learning Mid-level Filters for Person Re-identification | [
"Rui Zhao",
"Wanli Ouyang",
"Xiaogang Wang"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Zhao_Learning_Mid-level_Filters_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Zhao_Learning_Mid-level_Filters_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Zhao_2014_CVPR,author = {Zhao, Rui and Ouyang, Wanli and Wang, Xiaogang},title = {Learning Mid-level Filters for Person Re-identification},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | In this paper, we propose a novel approach of learning mid-level filters from automatically discovered patch clusters for person re-identification. It is well motivated by our study on what are good filters for person re-identification. Our mid-level filters are discriminatively learned for identifying specific visual ... | [
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19 | DeepReID: Deep Filter Pairing Neural Network for Person Re-Identification | [
"Wei Li",
"Rui Zhao",
"Tong Xiao",
"Xiaogang Wang"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Li_DeepReID_Deep_Filter_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Li_DeepReID_Deep_Filter_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Li_2014_CVPR,author = {Li, Wei and Zhao, Rui and Xiao, Tong and Wang, Xiaogang},title = {DeepReID: Deep Filter Pairing Neural Network for Person Re-Identification},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | Person re-identification is to match pedestrian images from disjoint camera views detected by pedestrian detectors. Challenges are presented in the form of complex variations of lightings, poses, viewpoints, blurring effects, image resolutions, camera settings, occlusions and background clutter across camera views. In ... | [
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20 | Lacunarity Analysis on Image Patterns for Texture Classification | [
"Yuhui Quan",
"Yong Xu",
"Yuping Sun",
"Yu Luo"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Quan_Lacunarity_Analysis_on_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Quan_Lacunarity_Analysis_on_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Quan_2014_CVPR,author = {Quan, Yuhui and Xu, Yong and Sun, Yuping and Luo, Yu},title = {Lacunarity Analysis on Image Patterns for Texture Classification},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | Based on the concept of lacunarity in fractal geometry, we developed a statistical approach to texture description, which yields highly discriminative feature with strong robustness to a wide range of transformations, including photometric changes and geometric changes. The texture feature is constructed by concatenati... | [
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21 | Segmentation-aware Deformable Part Models | [
"Eduard Trulls",
"Stavros Tsogkas",
"Iasonas Kokkinos",
"Alberto Sanfeliu",
"Francesc Moreno-Noguer"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Trulls_Segmentation-aware_Deformable_Part_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Trulls_Segmentation-aware_Deformable_Part_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Trulls_2014_CVPR,author = {Trulls, Eduard and Tsogkas, Stavros and Kokkinos, Iasonas and Sanfeliu, Alberto and Moreno-Noguer, Francesc},title = {Segmentation-aware Deformable Part Models},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},yea... | In this work we propose a technique to combine bottom-up segmentation, coming in the form of SLIC superpixels, with sliding window detectors, such as Deformable Part Models (DPMs). The merit of our approach lies in "cleaning up" the low-level HOG features by exploiting the spatial support of SLIC superpixels; this can... | [
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22 | From Categories to Individuals in Real Time -- A Unified Boosting Approach | [
"David Hall",
"Pietro Perona"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Hall_From_Categories_to_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Hall_From_Categories_to_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Hall_2014_CVPR,author = {Hall, David and Perona, Pietro},title = {From Categories to Individuals in Real Time -- A Unified Boosting Approach},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | A method for online, real-time learning of individual-object detectors is presented. Starting with a pre-trained boosted category detector, an individual-object detector is trained with near-zero computational cost. The individual detector is obtained by using the same feature cascade as the category detector along wit... | [
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23 | NMF-KNN: Image Annotation using Weighted Multi-view Non-negative Matrix Factorization | [
"Mahdi M. Kalayeh",
"Haroon Idrees",
"Mubarak Shah"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Kalayeh_NMF-KNN_Image_Annotation_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Kalayeh_NMF-KNN_Image_Annotation_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Kalayeh_2014_CVPR,author = {Kalayeh, Mahdi M. and Idrees, Haroon and Shah, Mubarak},title = {NMF-KNN: Image Annotation using Weighted Multi-view Non-negative Matrix Factorization},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {201... | The real world image databases such as Flickr are characterized by continuous addition of new images. The recent approaches for image annotation, i.e. the problem of assigning tags to images, have two major drawbacks. First, either models are learned using the entire training data, or to handle the issue of dataset imb... | [
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24 | Fine-Grained Visual Comparisons with Local Learning | [
"Aron Yu",
"Kristen Grauman"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Yu_Fine-Grained_Visual_Comparisons_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Yu_Fine-Grained_Visual_Comparisons_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Yu_2014_CVPR,author = {Yu, Aron and Grauman, Kristen},title = {Fine-Grained Visual Comparisons with Local Learning},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | Given two images, we want to predict which exhibits a particular visual attribute more than the other---even when the two images are quite similar. Existing relative attribute methods rely on global ranking functions; yet rarely will the visual cues relevant to a comparison be constant for all data, nor will humans' p... | [
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25 | Inferring Analogous Attributes | [
"Chao-Yeh Chen",
"Kristen Grauman"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Chen_Inferring_Analogous_Attributes_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Chen_Inferring_Analogous_Attributes_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Chen_2014_CVPR,author = {Chen, Chao-Yeh and Grauman, Kristen},title = {Inferring Analogous Attributes},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | The appearance of an attribute can vary considerably from class to class (e.g., a "fluffy" dog vs. a "fluffy" towel), making standard class-independent attribute models break down. Yet, training object-specific models for each attribute can be impractical, and defeats the purpose of using attributes to bridge category ... | [
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26 | Beyond Comparing Image Pairs: Setwise Active Learning for Relative Attributes | [
"Lucy Liang",
"Kristen Grauman"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Liang_Beyond_Comparing_Image_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Liang_Beyond_Comparing_Image_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Liang_2014_CVPR,author = {Liang, Lucy and Grauman, Kristen},title = {Beyond Comparing Image Pairs: Setwise Active Learning for Relative Attributes},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | It is useful to automatically compare images based on their visual properties---to predict which image is brighter, more feminine, more blurry, etc. However, comparative models are inherently more costly to train than their classification counterparts. Manually labeling all pairwise comparisons is intractable, so whi... | [
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27 | Visual Persuasion: Inferring Communicative Intents of Images | [
"Jungseock Joo",
"Weixin Li",
"Francis F. Steen",
"Song-Chun Zhu"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Joo_Visual_Persuasion_Inferring_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Joo_Visual_Persuasion_Inferring_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Joo_2014_CVPR,author = {Joo, Jungseock and Li, Weixin and Steen, Francis F. and Zhu, Song-Chun},title = {Visual Persuasion: Inferring Communicative Intents of Images},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | In this paper we introduce the novel problem of understanding visual persuasion. Modern mass media make extensive use of images to persuade people to make commercial and political decisions. These effects and techniques are widely studied in the social sciences, but behavioral studies do not scale to massive datasets. ... | [
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28 | Histograms of Pattern Sets for Image Classification and Object Recognition | [
"Winn Voravuthikunchai",
"Bruno Cremilleux",
"Frederic Jurie"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Voravuthikunchai_Histograms_of_Pattern_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Voravuthikunchai_Histograms_of_Pattern_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Voravuthikunchai_2014_CVPR,author = {Voravuthikunchai, Winn and Cremilleux, Bruno and Jurie, Frederic},title = {Histograms of Pattern Sets for Image Classification and Object Recognition},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},yea... | This paper introduces a novel image representation capturing feature dependencies through the mining of meaningful combinations of visual features. This representation leads to a compact and discriminative encoding of images that can be used for image classification, object detection or object recognition. The metho... | [
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29 | Incorporating Scene Context and Object Layout into Appearance Modeling | [
"Hamid Izadinia",
"Fereshteh Sadeghi",
"Ali Farhadi"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Izadinia_Incorporating_Scene_Context_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Izadinia_Incorporating_Scene_Context_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Izadinia_2014_CVPR,author = {Izadinia, Hamid and Sadeghi, Fereshteh and Farhadi, Ali},title = {Incorporating Scene Context and Object Layout into Appearance Modeling},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | A scene category imposes tight distributions over the kind of objects that might appear in the scene, the appearance of those objects and their layout. In this paper, we propose a method to learn scene structures that can encode three main interlacing components of a scene: the scene category, the context-specific appe... | [
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30 | Co-Segmentation of Textured 3D Shapes with Sparse Annotations | [
"Mehmet Ersin Yumer",
"Won Chun",
"Ameesh Makadia"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Yumer_Co-Segmentation_of_Textured_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Yumer_Co-Segmentation_of_Textured_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Yumer_2014_CVPR,author = {Ersin Yumer, Mehmet and Chun, Won and Makadia, Ameesh},title = {Co-Segmentation of Textured 3D Shapes with Sparse Annotations},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | We present a novel co-segmentation method for textured 3D shapes. Our algorithm takes a collection of textured shapes belonging to the same category and sparse annotations of foreground segments, and produces a joint dense segmentation of the shapes in the collection. We model the segments by a collectively trained Gau... | [
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31 | How to Evaluate Foreground Maps? | [
"Ran Margolin",
"Lihi Zelnik-Manor",
"Ayellet Tal"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Margolin_How_to_Evaluate_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Margolin_How_to_Evaluate_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Margolin_2014_CVPR,author = {Margolin, Ran and Zelnik-Manor, Lihi and Tal, Ayellet},title = {How to Evaluate Foreground Maps?},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | The output of many algorithms in computer-vision is either non-binary maps or binary maps (e.g., salient object detection and object segmentation). Several measures have been suggested to evaluate the accuracy of these foreground maps. In this paper, we show that the most commonly-used measures for evaluating both non-... | [
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32 | MILCut: A Sweeping Line Multiple Instance Learning Paradigm for Interactive Image Segmentation | [
"Jiajun Wu",
"Yibiao Zhao",
"Jun-Yan Zhu",
"Siwei Luo",
"Zhuowen Tu"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Wu_MILCut_A_Sweeping_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Wu_MILCut_A_Sweeping_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Wu_2014_CVPR,author = {Wu, Jiajun and Zhao, Yibiao and Zhu, Jun-Yan and Luo, Siwei and Tu, Zhuowen},title = {MILCut: A Sweeping Line Multiple Instance Learning Paradigm for Interactive Image Segmentation},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},m... | Interactive segmentation, in which a user provides a bounding box to an object of interest for image segmentation, has been applied to a variety of applications in image editing, crowdsourcing, computer vision, and medical imaging. The challenge of this semi-automatic image segmentation task lies in dealing with the un... | [
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33 | SCAMS: Simultaneous Clustering and Model Selection | [
"Zhuwen Li",
"Loong-Fah Cheong",
"Steven Zhiying Zhou"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Li_SCAMS_Simultaneous_Clustering_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Li_SCAMS_Simultaneous_Clustering_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Li_2014_CVPR,author = {Li, Zhuwen and Cheong, Loong-Fah and Zhiying Zhou, Steven},title = {SCAMS: Simultaneous Clustering and Model Selection},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | While clustering has been well studied in the past decade, model selection has drawn less attention. This paper addresses both problems in a joint manner with an indicator matrix formulation, in which the clustering cost is penalized by a Frobenius inner product term and the group number estimation is achieved by a ran... | [
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34 | The Shape-Time Random Field for Semantic Video Labeling | [
"Andrew Kae",
"Benjamin Marlin",
"Erik Learned-Miller"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Kae_The_Shape-Time_Random_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Kae_The_Shape-Time_Random_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Kae_2014_CVPR,author = {Kae, Andrew and Marlin, Benjamin and Learned-Miller, Erik},title = {The Shape-Time Random Field for Semantic Video Labeling},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | We propose a novel discriminative model for semantic labeling in videos by incorporating a prior to model both the shape and temporal dependencies of an object in video. A typical approach for this task is the conditional random field (CRF), which can model local interactions among adjacent regions in a video frame. Re... | [
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35 | The Secrets of Salient Object Segmentation | [
"Yin Li",
"Xiaodi Hou",
"Christof Koch",
"James M. Rehg",
"Alan L. Yuille"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Li_The_Secrets_of_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Li_The_Secrets_of_2014_CVPR_paper.pdf | null | 1406.2807 | title_snapshot | @InProceedings{Li_2014_CVPR,author = {Li, Yin and Hou, Xiaodi and Koch, Christof and Rehg, James M. and Yuille, Alan L.},title = {The Secrets of Salient Object Segmentation},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | In this paper we provide an extensive evaluation of fixation prediction and salient object segmentation algorithms as well as statistics of major datasets. Our analysis identifies serious design flaws of existing salient object benchmarks, called the dataset design bias, by over emphasising the stereotypical concepts o... | [
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36 | Non-rigid Segmentation using Sparse Low Dimensional Manifolds and Deep Belief Networks | [
"Jacinto C. Nascimento",
"Gustavo Carneiro"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Nascimento_Non-rigid_Segmentation_using_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Nascimento_Non-rigid_Segmentation_using_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Nascimento_2014_CVPR,author = {Nascimento, Jacinto C. and Carneiro, Gustavo},title = {Non-rigid Segmentation using Sparse Low Dimensional Manifolds and Deep Belief Networks},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | In this paper, we propose a new methodology for segmenting non-rigid visual objects, where the search procedure is onducted directly on a sparse low-dimensional manifold, guided by the classification results computed from a deep belief network. Our main contribution is the fact that we do not rely on the typical sub-d... | [
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37 | An Exemplar-based CRF for Multi-instance Object Segmentation | [
"Xuming He",
"Stephen Gould"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/He_An_Exemplar-based_CRF_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/He_An_Exemplar-based_CRF_2014_CVPR_paper.pdf | null | null | null | @InProceedings{He_2014_CVPR,author = {He, Xuming and Gould, Stephen},title = {An Exemplar-based CRF for Multi-instance Object Segmentation},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | We address the problem of joint detection and segmentation of multiple object instances in an image, a key step towards scene understanding. Inspired by data-driven methods, we propose an exemplar-based approach to the task of instance segmentation, in which a set of reference image/shape masks is used to find multiple... | [
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38 | Object Partitioning using Local Convexity | [
"Simon Christoph Stein",
"Markus Schoeler",
"Jeremie Papon",
"Florentin Worgotter"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Stein_Object_Partitioning_using_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Stein_Object_Partitioning_using_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Stein_2014_CVPR,author = {Christoph Stein, Simon and Schoeler, Markus and Papon, Jeremie and Worgotter, Florentin},title = {Object Partitioning using Local Convexity},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | The problem of how to arrive at an appropriate 3D-segmentation of a scene remains difficult. While current state-of-the-art methods continue to gradually improve in benchmark performance, they also grow more and more complex, for example by incorporating chains of classifiers, which require training on large manually a... | [
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39 | Bayesian Active Contours with Affine-Invariant, Elastic Shape Prior | [
"Darshan Bryner",
"Anuj Srivastava"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Bryner_Bayesian_Active_Contours_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Bryner_Bayesian_Active_Contours_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Bryner_2014_CVPR,author = {Bryner, Darshan and Srivastava, Anuj},title = {Bayesian Active Contours with Affine-Invariant, Elastic Shape Prior},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | Active contour, especially in conjunction with prior-shape models, has become an important tool in image segmentation. However, most contour methods use shape priors based on similarity-shape analysis, i.e. analysis that is invariant to rotation, translation, and scale. In practice, the training shapes used for prior-s... | [
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40 | Max-Margin Boltzmann Machines for Object Segmentation | [
"Jimei Yang",
"Simon Safar",
"Ming-Hsuan Yang"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Yang_Max-Margin_Boltzmann_Machines_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Yang_Max-Margin_Boltzmann_Machines_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Yang_2014_CVPR,author = {Yang, Jimei and Safar, Simon and Yang, Ming-Hsuan},title = {Max-Margin Boltzmann Machines for Object Segmentation},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | We present Max-Margin Boltzmann Machines (MMBMs) for object segmentation. MMBMs are essentially a class of Conditional Boltzmann Machines that model the joint distribution of hidden variables and output labels conditioned on input observations. In addition to image-to-label connections, we build direct image-to-hidden ... | [
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41 | Multiscale Combinatorial Grouping | [
"Pablo Arbelaez",
"Jordi Pont-Tuset",
"Jonathan T. Barron",
"Ferran Marques",
"Jitendra Malik"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Arbelaez_Multiscale_Combinatorial_Grouping_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Arbelaez_Multiscale_Combinatorial_Grouping_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Arbelaez_2014_CVPR,author = {Arbelaez, Pablo and Pont-Tuset, Jordi and Barron, Jonathan T. and Marques, Ferran and Malik, Jitendra},title = {Multiscale Combinatorial Grouping},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | We propose a unified approach for bottom-up hierarchical image segmentation and object candidate generation for recognition, called Multiscale Combinatorial Grouping (MCG). For this purpose, we first develop a fast normalized cuts algorithm. We then propose a high-performance hierarchical segmenter that makes effective... | [
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42 | RIGOR: Reusing Inference in Graph Cuts for Generating Object Regions | [
"Ahmad Humayun",
"Fuxin Li",
"James M. Rehg"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Humayun_RIGOR_Reusing_Inference_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Humayun_RIGOR_Reusing_Inference_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Humayun_2014_CVPR,author = {Humayun, Ahmad and Li, Fuxin and Rehg, James M.},title = {RIGOR: Reusing Inference in Graph Cuts for Generating Object Regions},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | Popular figure-ground segmentation algorithms generate a pool of boundary-aligned segment proposals that can be used in subsequent object recognition engines. These algorithms can recover most image objects with high accuracy, but are usually computationally intensive since many graph cuts are computed with different e... | [
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43 | Efficient Hierarchical Graph-Based Segmentation of RGBD Videos | [
"Steven Hickson",
"Stan Birchfield",
"Irfan Essa",
"Henrik Christensen"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Hickson_Efficient_Hierarchical_Graph-Based_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Hickson_Efficient_Hierarchical_Graph-Based_2014_CVPR_paper.pdf | null | 1801.08981 | title_snapshot | @InProceedings{Hickson_2014_CVPR,author = {Hickson, Steven and Birchfield, Stan and Essa, Irfan and Christensen, Henrik},title = {Efficient Hierarchical Graph-Based Segmentation of RGBD Videos},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014... | We present an efficient and scalable algorithm for segmenting 3D RGBD point clouds by combining depth, color, and temporal information using a multistage, hierarchical graph-based approach. Our algorithm processes a moving window over several point clouds to group similar regions over a graph, resulting in an initial ... | [
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44 | Point Matching in the Presence of Outliers in Both Point Sets: A Concave Optimization Approach | [
"Wei Lian",
"Lei Zhang"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Lian_Point_Matching_in_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Lian_Point_Matching_in_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Lian_2014_CVPR,author = {Lian, Wei and Zhang, Lei},title = {Point Matching in the Presence of Outliers in Both Point Sets: A Concave Optimization Approach},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | Recently, a concave optimization approach has been proposed to solve the robust point matching (RPM) problem. This method is globally optimal, but it requires that each model point has a counterpart in the data point set. Unfortunately, such a requirement may not be satisfied in certain applications when there are outl... | [
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45 | Multiple Structured-Instance Learning for Semantic Segmentation with Uncertain Training Data | [
"Feng-Ju Chang",
"Yen-Yu Lin",
"Kuang-Jui Hsu"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Chang_Multiple_Structured-Instance_Learning_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Chang_Multiple_Structured-Instance_Learning_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Chang_2014_CVPR,author = {Chang, Feng-Ju and Lin, Yen-Yu and Hsu, Kuang-Jui},title = {Multiple Structured-Instance Learning for Semantic Segmentation with Uncertain Training Data},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {201... | We present an approach MSIL-CRF that incorporates multiple instance learning (MIL) into conditional random fields (CRFs). It can generalize CRFs to work on training data with uncertain labels by the principle of MIL. In this work, it is applied to saving manual efforts on annotating training data for semantic segmentat... | [
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46 | Joint Motion Segmentation and Background Estimation in Dynamic Scenes | [
"Adeel Mumtaz",
"Weichen Zhang",
"Antoni B. Chan"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Mumtaz_Joint_Motion_Segmentation_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Mumtaz_Joint_Motion_Segmentation_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Mumtaz_2014_CVPR,author = {Mumtaz, Adeel and Zhang, Weichen and Chan, Antoni B.},title = {Joint Motion Segmentation and Background Estimation in Dynamic Scenes},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | We propose a joint foreground-background mixture model (FBM) that simultaneously performs background estimation and motion segmentation in complex dynamic scenes. Our FBM consist of a set of location-specific dynamic texture (DT) components, for modeling local background motion, and set of global DT components, for mod... | [
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47 | SeamSeg: Video Object Segmentation using Patch Seams | [
"S. Avinash Ramakanth",
"R. Venkatesh Babu"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Ramakanth_SeamSeg_Video_Object_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Ramakanth_SeamSeg_Video_Object_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Ramakanth_2014_CVPR,author = {Avinash Ramakanth, S. and Venkatesh Babu, R.},title = {SeamSeg: Video Object Segmentation using Patch Seams},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | In this paper, we propose a technique for video object segmentation using patch seams across frames. Typically, seams, which are connected paths of low energy, are utilised for retargeting, where the primary aim is to reduce the image size while preserving the salient image contents. Here, we adapt the formulation of ... | [
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48 | Laplacian Coordinates for Seeded Image Segmentation | [
"Wallace Casaca",
"Luis Gustavo Nonato",
"Gabriel Taubin"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Casaca_Laplacian_Coordinates_for_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Casaca_Laplacian_Coordinates_for_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Casaca_2014_CVPR,author = {Casaca, Wallace and Gustavo Nonato, Luis and Taubin, Gabriel},title = {Laplacian Coordinates for Seeded Image Segmentation},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | Seed-based image segmentation methods have gained much attention lately, mainly due to their good performance in segmenting complex images with little user interaction. Such popularity leveraged the development of many new variations of seed-based image segmentation techniques, which vary greatly regarding mathematical... | [
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49 | Error-tolerant Scribbles Based Interactive Image Segmentation | [
"Junjie Bai",
"Xiaodong Wu"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Bai_Error-tolerant_Scribbles_Based_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Bai_Error-tolerant_Scribbles_Based_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Bai_2014_CVPR,author = {Bai, Junjie and Wu, Xiaodong},title = {Error-tolerant Scribbles Based Interactive Image Segmentation},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | Scribbles in scribble-based interactive segmentation such as graph-cut are usually assumed to be perfectly accurate, i.e., foreground scribble pixels will never be segmented as background in the final segmentation. However, it can be hard to draw perfectly accurate scribbles, especially on fine structures of the image ... | [
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50 | Iterative Multilevel MRF Leveraging Context and Voxel Information for Brain Tumour Segmentation in MRI | [
"Nagesh Subbanna",
"Doina Precup",
"Tal Arbel"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Subbanna_Iterative_Multilevel_MRF_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Subbanna_Iterative_Multilevel_MRF_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Subbanna_2014_CVPR,author = {Subbanna, Nagesh and Precup, Doina and Arbel, Tal},title = {Iterative Multilevel MRF Leveraging Context and Voxel Information for Brain Tumour Segmentation in MRI},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June... | In this paper, we introduce a fully automated multistage graphical probabilistic framework to segment brain tumours from multimodal Magnetic Resonance Images (MRIs) acquired from real patients. An initial Bayesian tumour classification based on Gabor texture features permits subsequent computations to be focused on are... | [
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51 | Large Scale Multi-view Stereopsis Evaluation | [
"Rasmus Jensen",
"Anders Dahl",
"George Vogiatzis",
"Engin Tola",
"Henrik Aanaes"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Jensen_Large_Scale_Multi-view_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Jensen_Large_Scale_Multi-view_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Jensen_2014_CVPR,author = {Jensen, Rasmus and Dahl, Anders and Vogiatzis, George and Tola, Engin and Aanaes, Henrik},title = {Large Scale Multi-view Stereopsis Evaluation},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | The seminal multiple view stereo benchmark evaluations from Middlebury and by Strecha et al. have played a major role in propelling the development of multi-view stereopsis methodology. Although seminal, these benchmark datasets are limited in scope with few reference scenes. Here, we try to take these works a step fur... | [
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52 | Timing-Based Local Descriptor for Dynamic Surfaces | [
"Tony Tung",
"Takashi Matsuyama"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Tung_Timing-Based_Local_Descriptor_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Tung_Timing-Based_Local_Descriptor_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Tung_2014_CVPR,author = {Tung, Tony and Matsuyama, Takashi},title = {Timing-Based Local Descriptor for Dynamic Surfaces},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | In this paper, we present the first local descriptor designed for dynamic surfaces. A dynamic surface is a surface that can undergo non-rigid deformation (e.g., human body surface). Using state-of-the-art technology, details on dynamic surfaces such as cloth wrinkle or facial expression can be accurately reconstructed.... | [
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53 | A Minimal Solution to the Generalized Pose-and-Scale Problem | [
"Jonathan Ventura",
"Clemens Arth",
"Gerhard Reitmayr",
"Dieter Schmalstieg"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Ventura_A_Minimal_Solution_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Ventura_A_Minimal_Solution_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Ventura_2014_CVPR,author = {Ventura, Jonathan and Arth, Clemens and Reitmayr, Gerhard and Schmalstieg, Dieter},title = {A Minimal Solution to the Generalized Pose-and-Scale Problem},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2... | We propose a novel solution to the generalized camera pose problem which includes the internal scale of the generalized camera as an unknown parameter. This further generalization of the well-known absolute camera pose problem has applications in multi-frame loop closure. While a well-calibrated camera rig has a fixe... | [
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54 | A General and Simple Method for Camera Pose and Focal Length Determination | [
"Yinqiang Zheng",
"Shigeki Sugimoto",
"Imari Sato",
"Masatoshi Okutomi"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Zheng_A_General_and_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Zheng_A_General_and_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Zheng_2014_CVPR,author = {Zheng, Yinqiang and Sugimoto, Shigeki and Sato, Imari and Okutomi, Masatoshi},title = {A General and Simple Method for Camera Pose and Focal Length Determination},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},ye... | In this paper, we revisit the pose determination problem of a partially calibrated camera with unknown focal length, hereafter referred to as the PnPf problem, by using n (n ≥ 4) 3D-to-2D point correspondences. Our core contribution is to introduce the angle constraint and derive a compact bivariate polynomial equation... | [
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55 | Partial Symmetry in Polynomial Systems and its Applications in Computer Vision | [
"Yubin Kuang",
"Yinqiang Zheng",
"Kalle Astrom"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Kuang_Partial_Symmetry_in_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Kuang_Partial_Symmetry_in_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Kuang_2014_CVPR,author = {Kuang, Yubin and Zheng, Yinqiang and Astrom, Kalle},title = {Partial Symmetry in Polynomial Systems and its Applications in Computer Vision},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | Algorithms for solving systems of polynomial equations are key components for solving geometry problems in computer vision. Fast and stable polynomial solvers are essential for numerous applications e.g. minimal problems or finding for all stationary points of certain algebraic errors. Recently, full symmetry in the po... | [
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56 | Efficient Computation of Relative Pose for Multi-Camera Systems | [
"Laurent Kneip",
"Hongdong Li"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Kneip_Efficient_Computation_of_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Kneip_Efficient_Computation_of_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Kneip_2014_CVPR,author = {Kneip, Laurent and Li, Hongdong},title = {Efficient Computation of Relative Pose for Multi-Camera Systems},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | We present a novel solution to compute the relative pose of a generalized camera. Existing solutions are either not general, have too high computational complexity, or require too many correspondences, which impedes an efficient or accurate usage within Ransac schemes. We factorize the problem as a low-dimensional, ite... | [
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57 | Simultaneous Localization and Calibration: Self-Calibration of Consumer Depth Cameras | [
"Qian-Yi Zhou",
"Vladlen Koltun"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Zhou_Simultaneous_Localization_and_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Zhou_Simultaneous_Localization_and_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Zhou_2014_CVPR,author = {Zhou, Qian-Yi and Koltun, Vladlen},title = {Simultaneous Localization and Calibration: Self-Calibration of Consumer Depth Cameras},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | We describe an approach for simultaneous localization and calibration of a stream of range images. Our approach jointly optimizes the camera trajectory and a calibration function that corrects the camera's unknown nonlinear distortion. Experiments with real-world benchmark data and synthetic data show that our approach... | [
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58 | Minimal Scene Descriptions from Structure from Motion Models | [
"Song Cao",
"Noah Snavely"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Cao_Minimal_Scene_Descriptions_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Cao_Minimal_Scene_Descriptions_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Cao_2014_CVPR,author = {Cao, Song and Snavely, Noah},title = {Minimal Scene Descriptions from Structure from Motion Models},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | How much data do we need to describe a location? We explore this question in the context of 3D scene reconstructions created from running structure from motion on large Internet photo collections, where reconstructions can contain many millions of 3D points. We consider several methods for computing much more compact r... | [
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59 | Fast, Approximate Piecewise-Planar Modeling Based on Sparse Structure-from-Motion and Superpixels | [
"Andras Bodis-Szomoru",
"Hayko Riemenschneider",
"Luc Van Gool"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Bodis-Szomoru_Fast_Approximate_Piecewise-Planar_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Bodis-Szomoru_Fast_Approximate_Piecewise-Planar_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Bodis-Szomoru_2014_CVPR,author = {Bodis-Szomoru, Andras and Riemenschneider, Hayko and Van Gool, Luc},title = {Fast, Approximate Piecewise-Planar Modeling Based on Sparse Structure-from-Motion and Superpixels},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVP... | State-of-the-art Multi-View Stereo (MVS) algorithms deliver dense depth maps or complex meshes with very high detail, and redundancy over regular surfaces. In turn, our interest lies in an approximate, but light-weight method that is better to consider for large-scale applications, such as urban scene reconstruction fr... | [
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60 | On Projective Reconstruction In Arbitrary Dimensions | [
"Behrooz Nasihatkon",
"Richard Hartley",
"Jochen Trumpf"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Nasihatkon_On_Projective_Reconstruction_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Nasihatkon_On_Projective_Reconstruction_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Nasihatkon_2014_CVPR,author = {Nasihatkon, Behrooz and Hartley, Richard and Trumpf, Jochen},title = {On Projective Reconstruction In Arbitrary Dimensions},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | We study the theory of projective reconstruction for multiple projections from an arbitrary dimensional projective space into lower-dimensional spaces. This problem is important due to its applications in the analysis of dynamical scenes. The current theory, due to Hartley and Schaffalitzky, is based on the Grassmann t... | [
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61 | Stereo under Sequential Optimal Sampling: A Statistical Analysis Framework for Search Space Reduction | [
"Yilin Wang",
"Ke Wang",
"Enrique Dunn",
"Jan-Michael Frahm"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Wang_Stereo_under_Sequential_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Wang_Stereo_under_Sequential_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Wang_2014_CVPR,author = {Wang, Yilin and Wang, Ke and Dunn, Enrique and Frahm, Jan-Michael},title = {Stereo under Sequential Optimal Sampling: A Statistical Analysis Framework for Search Space Reduction},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},mo... | We develop a sequential optimal sampling framework for stereo disparity estimation by adapting the Sequential Probability Ratio Test (SPRT) model. We operate over local image neighborhoods by iteratively estimating single pixel disparity values until sufficient evidence has been gathered to either validate or contradic... | [
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62 | Efficient Pruning LMI Conditions for Branch-and-Prune Rank and Chirality-Constrained Estimation of the Dual Absolute Quadric | [
"Adlane Habed",
"Danda Pani Paudel",
"Cedric Demonceaux",
"David Fofi"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Habed_Efficient_Pruning_LMI_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Habed_Efficient_Pruning_LMI_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Habed_2014_CVPR,author = {Habed, Adlane and Pani Paudel, Danda and Demonceaux, Cedric and Fofi, David},title = {Efficient Pruning LMI Conditions for Branch-and-Prune Rank and Chirality-Constrained Estimation of the Dual Absolute Quadric},booktitle = {Proceedings of the IEEE Conference on Computer Vision ... | We present a new globally optimal algorithm for self-calibrating a moving camera with constant parameters. Our method aims at estimating the Dual Absolute Quadric (DAQ) under the rank-3 and, optionally, camera centers chirality constraints. We employ the Branch-and-Prune paradigm and explore the space of only 5 paramet... | [
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63 | Very Fast Solution to the PnP Problem with Algebraic Outlier Rejection | [
"Luis Ferraz",
"Xavier Binefa",
"Francesc Moreno-Noguer"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Ferraz_Very_Fast_Solution_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Ferraz_Very_Fast_Solution_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Ferraz_2014_CVPR,author = {Ferraz, Luis and Binefa, Xavier and Moreno-Noguer, Francesc},title = {Very Fast Solution to the PnP Problem with Algebraic Outlier Rejection},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | We propose a real-time, robust to outliers and accurate solution to the Perspective-n-Point (PnP) problem. The main advantages of our solution are twofold: first, it in- tegrates the outlier rejection within the pose estimation pipeline with a negligible computational overhead; and sec- ond, its scalability to arbitrar... | [
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64 | Finding Vanishing Points via Point Alignments in Image Primal and Dual Domains | [
"Jose Lezama",
"Rafael Grompone von Gioi",
"Gregory Randall",
"Jean-Michel Morel"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Lezama_Finding_Vanishing_Points_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Lezama_Finding_Vanishing_Points_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Lezama_2014_CVPR,author = {Lezama, Jose and Grompone von Gioi, Rafael and Randall, Gregory and Morel, Jean-Michel},title = {Finding Vanishing Points via Point Alignments in Image Primal and Dual Domains},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},mo... | We present a novel method for automatic vanishing point detection based on primal and dual point alignment detection. The very same point alignment detection algorithm is used twice: First in the image domain to group line segment endpoints into more precise lines. Second, it is used in the dual domain where converging... | [
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65 | Discriminative Feature-to-Point Matching in Image-Based Localization | [
"Michael Donoser",
"Dieter Schmalstieg"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Donoser_Discriminative_Feature-to-Point_Matching_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Donoser_Discriminative_Feature-to-Point_Matching_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Donoser_2014_CVPR,author = {Donoser, Michael and Schmalstieg, Dieter},title = {Discriminative Feature-to-Point Matching in Image-Based Localization},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | The prevalent approach to image-based localization is matching interest points detected in the query image to a sparse 3D point cloud representing the known world. The obtained correspondences are then used to recover a precise camera pose. The state-of-the-art in this field often ignores the availability of a set of 2... | [
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66 | Two-View Camera Housing Parameters Calibration for Multi-Layer Flat Refractive Interface | [
"Xida Chen",
"Yee-Hong Yang"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Chen_Two-View_Camera_Housing_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Chen_Two-View_Camera_Housing_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Chen_2014_CVPR,author = {Chen, Xida and Yang, Yee-Hong},title = {Two-View Camera Housing Parameters Calibration for Multi-Layer Flat Refractive Interface},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | In this paper, we present a novel refractive calibration method for an underwater stereo camera system where both cameras are looking through multiple parallel flat refractive interfaces. At the heart of our method is an important finding that the thickness of the interface can be estimated from a set of pixel correspo... | [
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67 | Accurate Localization and Pose Estimation for Large 3D Models | [
"Linus Svarm",
"Olof Enqvist",
"Magnus Oskarsson",
"Fredrik Kahl"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Svarm_Accurate_Localization_and_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Svarm_Accurate_Localization_and_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Svarm_2014_CVPR,author = {Svarm, Linus and Enqvist, Olof and Oskarsson, Magnus and Kahl, Fredrik},title = {Accurate Localization and Pose Estimation for Large 3D Models},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | We consider the problem of localizing a novel image in a large 3D model. In principle, this is just an instance of camera pose estimation, but the scale introduces some challenging problems. For one, it makes the correspondence problem very difficult and it is likely that there will be a significant rate of outliers to... | [
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68 | Relative Pose Estimation for a Multi-Camera System with Known Vertical Direction | [
"Gim Hee Lee",
"Marc Pollefeys",
"Friedrich Fraundorfer"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Lee_Relative_Pose_Estimation_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Lee_Relative_Pose_Estimation_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Lee_2014_CVPR,author = {Hee Lee, Gim and Pollefeys, Marc and Fraundorfer, Friedrich},title = {Relative Pose Estimation for a Multi-Camera System with Known Vertical Direction},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | In this paper, we present our minimal 4-point and linear 8-point algorithms to estimate the relative pose of a multi-camera system with known vertical directions, i.e. known absolute roll and pitch angles. We solve the minimal 4-point algorithm with the hidden variable resultant method and show that it leads to an 8-de... | [
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69 | Optimal Decisions from Probabilistic Models: The Intersection-over-Union Case | [
"Sebastian Nowozin"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Nowozin_Optimal_Decisions_from_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Nowozin_Optimal_Decisions_from_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Nowozin_2014_CVPR,author = {Nowozin, Sebastian},title = {Optimal Decisions from Probabilistic Models: The Intersection-over-Union Case},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | A probabilistic model allows us to reason about the world and make statistically optimal decisions using Bayesian decision theory. However, in practice the intractability of the decision problem forces us to adopt simplistic loss functions such as the 0/1 loss or Hamming loss and as result we make poor decisions throug... | [
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70 | Covariance Trees for 2D and 3D Processing | [
"Thierry Guillemot",
"Andres Almansa",
"Tamy Boubekeur"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Guillemot_Covariance_Trees_for_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Guillemot_Covariance_Trees_for_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Guillemot_2014_CVPR,author = {Guillemot, Thierry and Almansa, Andres and Boubekeur, Tamy},title = {Covariance Trees for 2D and 3D Processing},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | Gaussian Mixture Models have become one of the major tools in modern statistical image processing, and allowed performance breakthroughs in patch-based image denoising and restoration problems. Nevertheless, their adoption level was kept relatively low because of the computational cost associated to learning such model... | [
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71 | Hierarchical Subquery Evaluation for Active Learning on a Graph | [
"Oisin Mac Aodha",
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"Jan Kautz",
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] | https://openaccess.thecvf.com/content_cvpr_2014/html/Aodha_Hierarchical_Subquery_Evaluation_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Aodha_Hierarchical_Subquery_Evaluation_2014_CVPR_paper.pdf | null | 1504.08219 | title_snapshot | @InProceedings{Aodha_2014_CVPR,author = {Mac Aodha, Oisin and Campbell, Neill D.F. and Kautz, Jan and Brostow, Gabriel J.},title = {Hierarchical Subquery Evaluation for Active Learning on a Graph},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2... | To train good supervised and semi-supervised object classifiers, it is critical that we not waste the time of the human experts who are providing the training labels. Existing active learning strategies can have uneven performance, being efficient on some datasets but wasteful on others, or inconsistent just between ru... | [
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72 | Anytime Recognition of Objects and Scenes | [
"Sergey Karayev",
"Mario Fritz",
"Trevor Darrell"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Karayev_Anytime_Recognition_of_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Karayev_Anytime_Recognition_of_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Karayev_2014_CVPR,author = {Karayev, Sergey and Fritz, Mario and Darrell, Trevor},title = {Anytime Recognition of Objects and Scenes},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | Humans are capable of perceiving a scene at a glance, and obtain deeper understanding with additional time. Similarly, visual recognition deployments should be robust to varying computational budgets. Such situations require Anytime recognition ability, which is rarely considered in computer vision research. We present... | [
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73 | Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation | [
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"Trevor Darrell",
"Jitendra Malik"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Girshick_Rich_Feature_Hierarchies_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Girshick_Rich_Feature_Hierarchies_2014_CVPR_paper.pdf | null | 1311.2524 | title_snapshot | @InProceedings{Girshick_2014_CVPR,author = {Girshick, Ross and Donahue, Jeff and Darrell, Trevor and Malik, Jitendra},title = {Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {Jun... | Object detection performance, as measured on the canonical PASCAL VOC dataset, has plateaued in the last few years. The best-performing methods are complex ensemble systems that typically combine multiple low-level image features with high-level context. In this paper, we propose a simple and scalable detection algor... | [
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74 | Human Action Recognition by Representing 3D Skeletons as Points in a Lie Group | [
"Raviteja Vemulapalli",
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] | https://openaccess.thecvf.com/content_cvpr_2014/html/Vemulapalli_Human_Action_Recognition_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Vemulapalli_Human_Action_Recognition_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Vemulapalli_2014_CVPR,author = {Vemulapalli, Raviteja and Arrate, Felipe and Chellappa, Rama},title = {Human Action Recognition by Representing 3D Skeletons as Points in a Lie Group},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {... | Recently introduced cost-effective depth sensors coupled with the real-time skeleton estimation algorithm of Shotton et al. [16] have generated a renewed interest in skeleton-based human action recognition. Most of the existing skeleton-based approaches use either the joint locations or the joint angles to represent a ... | [
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75 | Multi-View Super Vector for Action Recognition | [
"Zhuowei Cai",
"Limin Wang",
"Xiaojiang Peng",
"Yu Qiao"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Cai_Multi-View_Super_Vector_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Cai_Multi-View_Super_Vector_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Cai_2014_CVPR,author = {Cai, Zhuowei and Wang, Limin and Peng, Xiaojiang and Qiao, Yu},title = {Multi-View Super Vector for Action Recognition},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | Images and videos are often characterized by multiple types of local descriptors such as SIFT, HOG and HOF, each of which describes certain aspects of object feature. Recognition systems benefit from fusing multiple types of these descriptors. Two widely applied fusion pipelines are descriptor concatenation and kernel ... | [
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76 | Unsupervised Spectral Dual Assignment Clustering of Human Actions in Context | [
"Simon Jones",
"Ling Shao"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Jones_Unsupervised_Spectral_Dual_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Jones_Unsupervised_Spectral_Dual_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Jones_2014_CVPR,author = {Jones, Simon and Shao, Ling},title = {Unsupervised Spectral Dual Assignment Clustering of Human Actions in Context},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | A recent trend of research has shown how contextual information related to an action, such as a scene or object, can enhance the accuracy of human action recognition systems. However, using context to improve unsupervised human action clustering has never been considered before, and cannot be achieved using existing cl... | [
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77 | Parsing Videos of Actions with Segmental Grammars | [
"Hamed Pirsiavash",
"Deva Ramanan"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Pirsiavash_Parsing_Videos_of_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Pirsiavash_Parsing_Videos_of_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Pirsiavash_2014_CVPR,author = {Pirsiavash, Hamed and Ramanan, Deva},title = {Parsing Videos of Actions with Segmental Grammars},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | Real-world videos of human activities exhibit temporal structure at various scales; long videos are typically composed out of multiple action instances, where each instance is itself composed of sub-actions with variable durations and orderings. Temporal grammars can presumably model such hierarchical structure, but ar... | [
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78 | Rate-Invariant Analysis of Trajectories on Riemannian Manifolds with Application in Visual Speech Recognition | [
"Jingyong Su",
"Anuj Srivastava",
"Fillipe D. M. de Souza",
"Sudeep Sarkar"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Su_Rate-Invariant_Analysis_of_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Su_Rate-Invariant_Analysis_of_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Su_2014_CVPR,author = {Su, Jingyong and Srivastava, Anuj and de Souza, Fillipe D. M. and Sarkar, Sudeep},title = {Rate-Invariant Analysis of Trajectories on Riemannian Manifolds with Application in Visual Speech Recognition},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern R... | In statistical analysis of video sequences for speech recognition, and more generally activity recognition, it is natural to treat temporal evolutions of features as trajectories on Riemannian manifolds. However, different evolution patterns result in arbitrary parameterizations of these trajectories. We investigate a ... | [
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79 | Piecewise Planar and Compact Floorplan Reconstruction from Images | [
"Ricardo Cabral",
"Yasutaka Furukawa"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Cabral_Piecewise_Planar_and_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Cabral_Piecewise_Planar_and_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Cabral_2014_CVPR,author = {Cabral, Ricardo and Furukawa, Yasutaka},title = {Piecewise Planar and Compact Floorplan Reconstruction from Images},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | This paper presents a system to reconstruct piecewise planar and compact floorplans from images, which are then converted to high quality texture-mapped models for free- viewpoint visualization. There are two main challenges in image-based floorplan reconstruction. The first is the lack of 3D information that can be ex... | [
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80 | Data-driven Flower Petal Modeling with Botany Priors | [
"Chenxi Zhang",
"Mao Ye",
"Bo Fu",
"Ruigang Yang"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Zhang_Data-driven_Flower_Petal_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Zhang_Data-driven_Flower_Petal_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Zhang_2014_CVPR,author = {Zhang, Chenxi and Ye, Mao and Fu, Bo and Yang, Ruigang},title = {Data-driven Flower Petal Modeling with Botany Priors},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | In this paper we focus on the 3D modeling of flower, in particular the petals. The complex structure, severe occlusions, and wide variations make the reconstruction of their 3D models a challenging task. Therefore, even though the flower is the most distinctive part of a plant, there has been little modeling study devo... | [
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81 | User-Specific Hand Modeling from Monocular Depth Sequences | [
"Jonathan Taylor",
"Richard Stebbing",
"Varun Ramakrishna",
"Cem Keskin",
"Jamie Shotton",
"Shahram Izadi",
"Aaron Hertzmann",
"Andrew Fitzgibbon"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Taylor_User-Specific_Hand_Modeling_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Taylor_User-Specific_Hand_Modeling_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Taylor_2014_CVPR,author = {Taylor, Jonathan and Stebbing, Richard and Ramakrishna, Varun and Keskin, Cem and Shotton, Jamie and Izadi, Shahram and Hertzmann, Aaron and Fitzgibbon, Andrew},title = {User-Specific Hand Modeling from Monocular Depth Sequences},booktitle = {Proceedings of the IEEE Conference ... | This paper presents a method for acquiring dense nonrigid shape and deformation from a single monocular depth sensor. We focus on modeling the human hand, and assume that a single rough template model is available. We combine and extend existing work on model-based tracking, subdivision surface fitting, and mesh deform... | [
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82 | Class Specific 3D Object Shape Priors Using Surface Normals | [
"Christian Hane",
"Nikolay Savinov",
"Marc Pollefeys"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Hane_Class_Specific_3D_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Hane_Class_Specific_3D_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Hane_2014_CVPR,author = {Hane, Christian and Savinov, Nikolay and Pollefeys, Marc},title = {Class Specific 3D Object Shape Priors Using Surface Normals},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | Dense 3D reconstruction of real world objects containing textureless, reflective and specular parts is a challenging task. Using general smoothness priors such as surface area regularization can lead to defects in the form of disconnected parts or unwanted indentations. We argue that this problem can be solved by explo... | [
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83 | Frequency-Based 3D Reconstruction of Transparent and Specular Objects | [
"Ding Liu",
"Xida Chen",
"Yee-Hong Yang"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Liu_Frequency-Based_3D_Reconstruction_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Liu_Frequency-Based_3D_Reconstruction_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Liu_2014_CVPR,author = {Liu, Ding and Chen, Xida and Yang, Yee-Hong},title = {Frequency-Based 3D Reconstruction of Transparent and Specular Objects},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | 3D reconstruction of transparent and specular objects is a very challenging topic in computer vision. For transparent and specular objects, which have complex interior and exterior structures that can reflect and refract light in a complex fashion, it is difficult, if not impossible, to use either passive stereo or the... | [
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84 | Human Body Shape Estimation Using a Multi-Resolution Manifold Forest | [
"Frank Perbet",
"Sam Johnson",
"Minh-Tri Pham",
"Bjorn Stenger"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Perbet_Human_Body_Shape_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Perbet_Human_Body_Shape_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Perbet_2014_CVPR,author = {Perbet, Frank and Johnson, Sam and Pham, Minh-Tri and Stenger, Bjorn},title = {Human Body Shape Estimation Using a Multi-Resolution Manifold Forest},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | This paper proposes a method for estimating the 3D body shape of a person with robustness to clothing. We formulate the problem as optimization over the manifold of valid depth maps of body shapes learned from synthetic training data. The manifold itself is represented using a novel data structure, a Multi-Resolution M... | [
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85 | Quality Dynamic Human Body Modeling Using a Single Low-cost Depth Camera | [
"Qing Zhang",
"Bo Fu",
"Mao Ye",
"Ruigang Yang"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Zhang_Quality_Dynamic_Human_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Zhang_Quality_Dynamic_Human_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Zhang_2014_CVPR,author = {Zhang, Qing and Fu, Bo and Ye, Mao and Yang, Ruigang},title = {Quality Dynamic Human Body Modeling Using a Single Low-cost Depth Camera},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | In this paper we present a novel autonomous pipeline to build a personalized parametric model (pose-driven avatar) using a single depth sensor. Our method first captures a few high-quality scans of the user rotating herself at multiple poses from different views. We fit each incomplete scan using template fitting techn... | [
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86 | Single-View 3D Scene Parsing by Attributed Grammar | [
"Xiaobai Liu",
"Yibiao Zhao",
"Song-Chun Zhu"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Liu_Single-View_3D_Scene_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Liu_Single-View_3D_Scene_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Liu_2014_CVPR,author = {Liu, Xiaobai and Zhao, Yibiao and Zhu, Song-Chun},title = {Single-View 3D Scene Parsing by Attributed Grammar},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | In this paper, we present an attributed grammar for parsing man-made outdoor scenes into semantic surfaces, and recovering its 3D model simultaneously. The grammar takes superpixels as its terminal nodes and use five production rules to generate the scene into a hierarchical parse graph. Each graph node actually correl... | [
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87 | Separation of Line Drawings Based on Split Faces for 3D Object Reconstruction | [
"Changqing Zou",
"Heng Yang",
"Jianzhuang Liu"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Zou_Separation_of_Line_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Zou_Separation_of_Line_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Zou_2014_CVPR,author = {Zou, Changqing and Yang, Heng and Liu, Jianzhuang},title = {Separation of Line Drawings Based on Split Faces for 3D Object Reconstruction},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | Reconstructing 3D objects from single line drawings is often desirable in computer vision and graphics applications. If the line drawing of a complex 3D object is decomposed into primitives of simple shape, the object can be easily reconstructed. We propose an effective method to conduct the line drawing separation and... | [
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88 | When 3D Reconstruction Meets Ubiquitous RGB-D Images | [
"Quanshi Zhang",
"Xuan Song",
"Xiaowei Shao",
"Huijing Zhao",
"Ryosuke Shibasaki"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Zhang_When_3D_Reconstruction_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Zhang_When_3D_Reconstruction_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Zhang_2014_CVPR,author = {Zhang, Quanshi and Song, Xuan and Shao, Xiaowei and Zhao, Huijing and Shibasaki, Ryosuke},title = {When 3D Reconstruction Meets Ubiquitous RGB-D Images},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014... | 3D reconstruction from a single image is a classical problem in computer vision. However, it still poses great challenges for the reconstruction of daily-use objects with irregular shapes. In this paper, we propose to learn 3D reconstruction knowledge from informally captured RGB-D images, which will probably be ubiqui... | [
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89 | Stable Template-Based Isometric 3D Reconstruction in All Imaging Conditions by Linear Least-Squares | [
"Ajad Chhatkuli",
"Daniel Pizarro",
"Adrien Bartoli"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Chhatkuli_Stable_Template-Based_Isometric_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Chhatkuli_Stable_Template-Based_Isometric_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Chhatkuli_2014_CVPR,author = {Chhatkuli, Ajad and Pizarro, Daniel and Bartoli, Adrien},title = {Stable Template-Based Isometric 3D Reconstruction in All Imaging Conditions by Linear Least-Squares},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {... | It has been recently shown that reconstructing an isometric surface from a single 2D input image matched to a 3D template was a well-posed problem. This however does not tell us how reconstruction algorithms will behave in practical conditions, where the amount of perspective is generally small and the projection thus ... | [
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90 | Discrete-Continuous Depth Estimation from a Single Image | [
"Miaomiao Liu",
"Mathieu Salzmann",
"Xuming He"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Liu_Discrete-Continuous_Depth_Estimation_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Liu_Discrete-Continuous_Depth_Estimation_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Liu_2014_CVPR,author = {Liu, Miaomiao and Salzmann, Mathieu and He, Xuming},title = {Discrete-Continuous Depth Estimation from a Single Image},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | In this paper, we tackle the problem of estimating the depth of a scene from a single image. This is a challenging task, since a single image on its own does not provide any depth cue. To address this, we exploit the availability of a pool of images for which the depth is known. More specifically, we formulate monocula... | [
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91 | Leveraging Hierarchical Parametric Networks for Skeletal Joints Based Action Segmentation and Recognition | [
"Di Wu",
"Ling Shao"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Wu_Leveraging_Hierarchical_Parametric_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Wu_Leveraging_Hierarchical_Parametric_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Wu_2014_CVPR,author = {Wu, Di and Shao, Ling},title = {Leveraging Hierarchical Parametric Networks for Skeletal Joints Based Action Segmentation and Recognition},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | Over the last few years, with the immense popularity of the Kinect, there has been renewed interest in developing methods for human gesture and action recognition from 3D skeletal data. A number of approaches have been proposed to extract representative features from 3D skeletal data, most commonly hard wired geometric... | [
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92 | Seeing What You're Told: Sentence-Guided Activity Recognition In Video | [
"Narayanaswamy Siddharth",
"Andrei Barbu",
"Jeffrey Mark Siskind"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Siddharth_Seeing_What_Youre_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Siddharth_Seeing_What_Youre_2014_CVPR_paper.pdf | null | 1308.4189 | title_snapshot | @InProceedings{Siddharth_2014_CVPR,author = {Siddharth, Narayanaswamy and Barbu, Andrei and Mark Siskind, Jeffrey},title = {Seeing What You're Told: Sentence-Guided Activity Recognition In Video},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {20... | We present a system that demonstrates how the compositional structure of events, in concert with the compositional structure of language, can interplay with the underlying focusing mechanisms in video action recognition, providing a medium for top-down and bottom-up integration as well as multi-modal integration betwee... | [
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93 | Action Localization with Tubelets from Motion | [
"Mihir Jain",
"Jan van Gemert",
"Herve Jegou",
"Patrick Bouthemy",
"Cees G.M. Snoek"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Jain_Action_Localization_with_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Jain_Action_Localization_with_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Jain_2014_CVPR,author = {Jain, Mihir and van Gemert, Jan and Jegou, Herve and Bouthemy, Patrick and Snoek, Cees G.M.},title = {Action Localization with Tubelets from Motion},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | This paper considers the problem of action localization, where the objective is to determine when and where certain actions appear. We introduce a sampling strategy to produce 2D+t sequences of bounding boxes, called tubelets. Compared to state-of-the-art alternatives, this drastically reduces the number of hypotheses ... | [
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94 | Actionness Ranking with Lattice Conditional Ordinal Random Fields | [
"Wei Chen",
"Caiming Xiong",
"Ran Xu",
"Jason J. Corso"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Chen_Actionness_Ranking_with_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Chen_Actionness_Ranking_with_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Chen_2014_CVPR,author = {Chen, Wei and Xiong, Caiming and Xu, Ran and Corso, Jason J.},title = {Actionness Ranking with Lattice Conditional Ordinal Random Fields},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | Action analysis in image and video has been attracting more and more attention in computer vision. Recognizing specific actions in video clips has been the main focus. We move in a new, more general direction in this paper and ask the critical fundamental question: what is action, how is action different from motion,... | [
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95 | Multiple Granularity Analysis for Fine-grained Action Detection | [
"Bingbing Ni",
"Vignesh R. Paramathayalan",
"Pierre Moulin"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Ni_Multiple_Granularity_Analysis_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Ni_Multiple_Granularity_Analysis_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Ni_2014_CVPR,author = {Ni, Bingbing and Paramathayalan, Vignesh R. and Moulin, Pierre},title = {Multiple Granularity Analysis for Fine-grained Action Detection},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | We propose to decompose the fine-grained human activity analysis problem into two sequential tasks with increasing granularity. Firstly, we infer the coarse interaction status, i.e., which object is being manipulated and where it is. Knowing that the major challenge is frequent mutual occlusions during manipulation, we... | [
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96 | Human Action Recognition Across Datasets by Foreground-weighted Histogram Decomposition | [
"Waqas Sultani",
"Imran Saleemi"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Sultani_Human_Action_Recognition_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Sultani_Human_Action_Recognition_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Sultani_2014_CVPR,author = {Sultani, Waqas and Saleemi, Imran},title = {Human Action Recognition Across Datasets by Foreground-weighted Histogram Decomposition},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | This paper attempts to address the problem of recognizing human actions while training and testing on distinct datasets, when test videos are neither labeled nor available during training. In this scenario, learning of a joint vocabulary, or domain transfer techniques are not applicable. We first explore reasons for po... | [
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97 | Range-Sample Depth Feature for Action Recognition | [
"Cewu Lu",
"Jiaya Jia",
"Chi-Keung Tang"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Lu_Range-Sample_Depth_Feature_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Lu_Range-Sample_Depth_Feature_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Lu_2014_CVPR,author = {Lu, Cewu and Jia, Jiaya and Tang, Chi-Keung},title = {Range-Sample Depth Feature for Action Recognition},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {2014}} | We propose binary range-sample feature in depth. It is based on t tests and achieves reasonable invariance with respect to possible change in scale, viewpoint, and background. It is robust to occlusion and data corruption as well. The descriptor works in a high speed thanks to its binary property. Working together with... | [
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98 | The Language of Actions: Recovering the Syntax and Semantics of Goal-Directed Human Activities | [
"Hilde Kuehne",
"Ali Arslan",
"Thomas Serre"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Kuehne_The_Language_of_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Kuehne_The_Language_of_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Kuehne_2014_CVPR,author = {Kuehne, Hilde and Arslan, Ali and Serre, Thomas},title = {The Language of Actions: Recovering the Syntax and Semantics of Goal-Directed Human Activities},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month = {June},year = {20... | This paper describes a framework for modeling human activities as temporally structured processes. Our approach is motivated by the inherently hierarchical nature of human activities and the close correspondence between human actions and speech: We model action units using Hidden Markov Models, much like words in speec... | [
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99 | Complex Activity Recognition using Granger Constrained DBN (GCDBN) in Sports and Surveillance Video | [
"Eran Swears",
"Anthony Hoogs",
"Qiang Ji",
"Kim Boyer"
] | https://openaccess.thecvf.com/content_cvpr_2014/html/Swears_Complex_Activity_Recognition_2014_CVPR_paper.html | https://openaccess.thecvf.com/content_cvpr_2014/papers/Swears_Complex_Activity_Recognition_2014_CVPR_paper.pdf | null | null | null | @InProceedings{Swears_2014_CVPR,author = {Swears, Eran and Hoogs, Anthony and Ji, Qiang and Boyer, Kim},title = {Complex Activity Recognition using Granger Constrained DBN (GCDBN) in Sports and Surveillance Video},booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},month =... | Modeling interactions of multiple co-occurring objects in a complex activity is becoming increasingly popular in the video domain. The Dynamic Bayesian Network (DBN) has been applied to this problem in the past due to its natural ability to statistically capture complex temporal dependencies. However, standard DBN stru... | [
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