paper_id uint32 0 1.64k | title stringlengths 15 155 | authors listlengths 1 18 | ecva_url stringlengths 76 79 | pdf_url stringlengths 70 70 | supp_url stringlengths 75 75 ⌀ | doi stringlengths 25 28 | arxiv_id stringlengths 10 10 ⌀ | arxiv_id_source stringclasses 2
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0 | Learning Depth from Focus in the Wild | [
"Changyeon Won",
"Hae-Gon Jeon"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/19_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610001.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610001-supp.pdf | 10.1007/978-3-031-19769-7_1 | 2207.09658 | title_snapshot | For better photography, most recent commercial cameras including smartphones have either adopted large-aperture lens to collect more light or used a burst mode to take multiple images within short times. These interesting features lead us to examine depth from focus/defocus. In this work, we present a convolutional neu... | [
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1 | Learning-Based Point Cloud Registration for 6D Object Pose Estimation in the Real World | [
"Zheng Dang",
"Lizhou Wang",
"Yu Guo",
"Mathieu Salzmann"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/69_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610018.pdf | null | 10.1007/978-3-031-19769-7_2 | 2203.15309 | title_judge | In this work, we tackle the task of estimating the 6D pose of an object from point cloud data. While recent learning-based approaches to addressing this task have shown great success on synthetic datasets, we have observed them to fail in the presence of real-world data. We thus analyze the causes of these failures, wh... | [
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2 | An End-to-End Transformer Model for Crowd Localization | [
"Dingkang Liang",
"Wei Xu",
"Xiang Bai"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/127_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610037.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610037-supp.pdf | 10.1007/978-3-031-19769-7_3 | 2202.13065 | title_snapshot | Crowd localization, predicting head positions, is a more practical and high-level task than simply counting. Existing methods employ pseudo-bounding boxes or pre-designed localization maps, relying on complex post-processing to obtain the head positions. In this paper, we propose an elegant, end-to-end Crowd Localizati... | [
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3 | Few-Shot Single-View 3D Reconstruction with Memory Prior Contrastive Network | [
"Zhen Xing",
"Yijiang Chen",
"Zhixin Ling",
"Xiangdong Zhou",
"Yu Xiang"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/192_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610054.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610054-supp.pdf | 10.1007/978-3-031-19769-7_4 | 2208.00183 | title_snapshot | 3D reconstruction of novel categories based on few-shot learning is appealing in real-world applications and attracts increasing research interests. Previous approaches mainly focus on how to design shape prior models for different categories. Their performance on unseen categories is not very competitive. In this pape... | [
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4 | DID-M3D: Decoupling Instance Depth for Monocular 3D Object Detection | [
"Liang Peng",
"Xiaopei Wu",
"Zheng Yang",
"Haifeng Liu",
"Deng Cai"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/343_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610071.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610071-supp.pdf | 10.1007/978-3-031-19769-7_5 | 2207.08531 | title_snapshot | Monocular 3D detection has drawn much attention from the community due to its low cost and setup simplicity. It takes an RGB image as input and predicts 3D boxes in the 3D space. The most challenging sub-task lies in the instance depth estimation. Previous works usually use a direct estimation method. However, in this ... | [
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5 | Adaptive Co-Teaching for Unsupervised Monocular Depth Estimation | [
"Weisong Ren",
"Lijun Wang",
"Yongri Piao",
"Miao Zhang",
"Huchuan Lu",
"Ting Liu"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/405_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610089.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610089-supp.pdf | 10.1007/978-3-031-19769-7_6 | null | null | Unsupervised depth estimation using photometric losses suffers from local minimum and training instability. We address this issue by proposing an adaptive co-teaching framework to distill the learned knowledge from unsupervised teacher networks to a student network. We design an ensemble architecture for our teacher ne... | [
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6 | Fusing Local Similarities for Retrieval-Based 3D Orientation Estimation of Unseen Objects | [
"Chen Zhao",
"Yinlin Hu",
"Mathieu Salzmann"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/444_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610106.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610106-supp.pdf | 10.1007/978-3-031-19769-7_7 | 2203.08472 | title_snapshot | In this paper, we tackle the task of estimating the 3D orientation of previously-unseen objects from monocular images. This task contrasts with the one considered by most existing deep learning methods which typically assume that the testing objects have been observed during training. To handle the unseen objects, we f... | [
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7 | Lidar Point Cloud Guided Monocular 3D Object Detection | [
"Liang Peng",
"Fei Liu",
"Zhengxu Yu",
"Senbo Yan",
"Dan Deng",
"Zheng Yang",
"Haifeng Liu",
"Deng Cai"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/655_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610123.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610123-supp.pdf | 10.1007/978-3-031-19769-7_8 | 2104.09035 | title_snapshot | Monocular 3D object detection is a challenging task in the self-driving and computer vision community. As a common practice, most previous works use manually annotated 3D box labels, where the annotating process is expensive. In this paper, we find that the precisely and carefully annotated labels may be unnecessary in... | [
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8 | Structural Causal 3D Reconstruction | [
"Weiyang Liu",
"Zhen Liu",
"Liam Paull",
"Adrian Weller",
"Bernhard Schölkopf"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/656_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610140.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610140-supp.pdf | 10.1007/978-3-031-19769-7_9 | 2207.10156 | title_snapshot | This paper considers the problem of unsupervised 3D object reconstruction from in-the-wild single-view images. Due to ambiguity and intrinsic ill-posedness, this problem is inherently difficult to solve and therefore requires strong regularization to achieve disentanglement of different latent factors. Unlike existing ... | [
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9 | 3D Human Pose Estimation Using Möbius Graph Convolutional Networks | [
"Niloofar Azizi",
"Horst Possegger",
"Emanuele Rodolà",
"Horst Bischof"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/1049_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610158.pdf | null | 10.1007/978-3-031-19769-7_10 | 2203.10554 | title_snapshot | 3D human pose estimation is fundamental to understanding human behavior. Recently, promising results have been achieved by graph convolutional networks(GCNs), which achieve state-of-the-art performance and provide rather light-weight architectures. However, a major limitation of GCNs is their inability to encode all th... | [
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10 | Learning to Train a Point Cloud Reconstruction Network without Matching | [
"Tianxin Huang",
"Xuemeng Yang",
"Jiangning Zhang",
"Jinhao Cui",
"Hao Zou",
"Jun Chen",
"Xiangrui Zhao",
"Yong Liu"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/1235_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610177.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610177-supp.pdf | 10.1007/978-3-031-19769-7_11 | null | null | Reconstruction networks for well-ordered data such as 2D images and 1D continuous signals are easy to optimize through element-wised squared errors, while permutation-arbitrary point clouds cannot be constrained directly because their points permutations are not fixed. Though existing works design algorithms to match t... | [
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11 | PanoFormer: Panorama Transformer for Indoor 360° Depth Estimation | [
"Zhijie Shen",
"Chunyu Lin",
"Kang Liao",
"Lang Nie",
"Zishuo Zheng",
"Yao Zhao"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/1300_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610193.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610193-supp.pdf | 10.1007/978-3-031-19769-7_12 | 2203.09283 | title_snapshot | Existing panoramic depth estimation methods based on convolutional neural networks (CNNs) focus on removing panoramic distortions, failing to perceive panoramic structures efficiently due to the fixed receptive field in CNNs. This paper proposes the panorama Transformer (named PanoFormer) to estimate the depth in panor... | [
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12 | Self-supervised Human Mesh Recovery with Cross-Representation Alignment | [
"Xuan Gong",
"Meng Zheng",
"Benjamin Planche",
"Srikrishna Karanam",
"Terrence Chen",
"David Doermann",
"Ziyan Wu"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/1534_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610210.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610210-supp.pdf | 10.1007/978-3-031-19769-7_13 | 2209.04596 | title_snapshot | Fully supervised human mesh recovery methods are data-hungry and have poor generalizability due to the limited availability and diversity of 3D-annotated benchmark datasets. Recent progress in self-supervised human mesh recovery has been made using synthetic-data-driven training paradigms where the model is trained fro... | [
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13 | AlignSDF: Pose-Aligned Signed Distance Fields for Hand-Object Reconstruction | [
"Zerui Chen",
"Yana Hasson",
"Cordelia Schmid",
"Ivan Laptev"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/1549_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610229.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610229-supp.zip | 10.1007/978-3-031-19769-7_14 | 2207.12909 | title_snapshot | Recent work achieved impressive progress towards joint reconstruction of hands and manipulated objects from monocular color images. Existing methods focus on two alternative representations in terms of either parametric meshes or signed distance fields (SDFs). On one side, parametric models can benefit from prior knowl... | [
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14 | A Reliable Online Method for Joint Estimation of Focal Length and Camera Rotation | [
"Yiming Qian",
"James H. Elder"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/1737_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610247.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610247-supp.pdf | 10.1007/978-3-031-19769-7_15 | 2207.12934 | title_snapshot | Linear perspective cues deriving from regularities of the built environment can be used to recalibrate both intrinsic and extrinsic camera parameters online, but these estimates can be unreliable due to irregularities in the scene, uncertainties in line segment estimation and background clutter. Here we address this ch... | [
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15 | PS-NeRF: Neural Inverse Rendering for Multi-View Photometric Stereo | [
"Wenqi Yang",
"Guanying Chen",
"Chaofeng Chen",
"Zhenfang Chen",
"Kwan-Yee K. Wong"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/1832_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610263.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610263-supp.pdf | 10.1007/978-3-031-19769-7_16 | 2207.11406 | title_snapshot | Traditional multi-view photometric stereo (MVPS) methods are often composed of multiple disjoint stages, resulting in noticeable accumulated errors. In this paper, we present a neural inverse rendering method for MVPS based on implicit representation. Given multi-view images of a non-Lambertian object illuminated by mu... | [
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16 | Share with Thy Neighbors: Single-View Reconstruction by Cross-Instance Consistency | [
"Tom Monnier",
"Matthew Fisher",
"Alexei A. Efros",
"Mathieu Aubry"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/1851_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610282.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610282-supp.pdf | 10.1007/978-3-031-19769-7_17 | 2204.10310 | title_snapshot | Approaches for single-view reconstruction typically rely on viewpoint annotations, silhouettes, the absence of background, multiple views of the same instance, a template shape, or symmetry. We avoid all such supervision and assumptions by explicitly leveraging the consistency between images of different object instanc... | [
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17 | Towards Comprehensive Representation Enhancement in Semantics-Guided Self-Supervised Monocular Depth Estimation | [
"Jingyuan Ma",
"Xiangyu Lei",
"Nan Liu",
"Xian Zhao",
"Shiliang Pu"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/1925_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610299.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610299-supp.zip | 10.1007/978-3-031-19769-7_18 | null | null | Semantics-guided self-supervised monocular depth estimation has been widely researched, owing to the strong cross-task correlation of depth and semantics. However, since depth estimation and semantic segmentation are fundamentally two types of tasks: one is regression while the other is classification, the distribution... | [
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18 | AvatarCap: Animatable Avatar Conditioned Monocular Human Volumetric Capture | [
"Zhe Li",
"Zerong Zheng",
"Hongwen Zhang",
"Chaonan Ji",
"Yebin Liu"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/2057_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610317.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610317-supp.pdf | 10.1007/978-3-031-19769-7_19 | 2207.02031 | title_snapshot | To address the ill-posed problem caused by partial observations in monocular human volumetric capture, we present AvatarCap, a novel framework that introduces animatable avatars into the capture pipeline for high-fidelity reconstruction in both visible and invisible regions. Our method firstly creates an animatable ava... | [
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19 | Cross-Attention of Disentangled Modalities for 3D Human Mesh Recovery with Transformers | [
"Junhyeong Cho",
"Kim Youwang",
"Tae-Hyun Oh"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/2116_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610336.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610336-supp.pdf | 10.1007/978-3-031-19769-7_20 | 2207.13820 | title_snapshot | Transformer encoder architectures have recently achieved state-of-the-art results on monocular 3D human mesh reconstruction, but they require a substantial number of parameters and expensive computations. Due to the large memory overhead and slow inference speed, it is difficult to deploy such models for practical use.... | [
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20 | GeoRefine: Self-Supervised Online Depth Refinement for Accurate Dense Mapping | [
"Pan Ji",
"Qingan Yan",
"Yuxin Ma",
"Yi Xu"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/2124_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610354.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610354-supp.pdf | 10.1007/978-3-031-19769-7_21 | 2205.01656 | title_snapshot | We present a robust and accurate depth refinement system, named GeoRefine, for geometrically-consistent dense mapping from monocular sequences. GeoRefine consists of three modules: a hybrid SLAM module using learning-based priors, an online depth refinement module leveraging self-supervision, and a global mapping modul... | [
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21 | Multi-modal Masked Pre-training for Monocular Panoramic Depth Completion | [
"Zhiqiang Yan",
"Xiang Li",
"Kun Wang",
"Zhenyu Zhang",
"Jun Li",
"Jian Yang"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/2269_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610372.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610372-supp.pdf | 10.1007/978-3-031-19769-7_22 | 2203.09855 | title_snapshot | In this paper, we formulate a potentially valuable panoramic depth completion (PDC) task as panoramic 3D cameras often produce 360° depth with missing data in complex scenes. Its goal is to recover dense panoramic depths from raw sparse ones and panoramic RGB images. To deal with the PDC task, we train a deep network ... | [
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22 | GitNet: Geometric Prior-Based Transformation for Birds-Eye-View Segmentation | [
"Shi Gong",
"Xiaoqing Ye",
"Xiao Tan",
"Jingdong Wang",
"Errui Ding",
"Yu Zhou",
"Xiang Bai"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/2449_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610390.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610390-supp.pdf | 10.1007/978-3-031-19769-7_23 | 2204.07733 | title_snapshot | Birds-eye-view (BEV) semantic segmentation is critical for autonomous driving for its powerful spatial representation ability. It is challenging to estimate the BEV semantic maps from monocular images due to the spatial gap, since it is implicitly required to realize both the perspective-to-BEV transformation and segme... | [
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23 | Learning Visibility for Robust Dense Human Body Estimation | [
"Chun-Han Yao",
"Jimei Yang",
"Duygu Ceylan",
"Yi Zhou",
"Yang Zhou",
"Ming-Hsuan Yang"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/2568_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610406.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610406-supp.pdf | 10.1007/978-3-031-19769-7_24 | 2208.10652 | title_snapshot | Estimating 3D human pose and shape from 2D images is a crucial yet challenging task. While prior methods with model-based representations can perform reasonably well on whole-body images, they often fail when parts of the body are occluded or outside the frame. Moreover, these results usually do not faithfully capture ... | [
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24 | Towards High-Fidelity Single-View Holistic Reconstruction of Indoor Scenes | [
"Haolin Liu",
"Yujian Zheng",
"Guanying Chen",
"Shuguang Cui",
"Xiaoguang Han"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/2747_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610423.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610423-supp.pdf | 10.1007/978-3-031-19769-7_25 | 2207.08656 | title_snapshot | We present a new framework to reconstruct holistic 3D indoor scenes including both room background and indoor objects from single-view images. Existing methods can only produce 3D shapes of indoor objects with limited geometry quality because of the heavy occlusion of indoor scenes. To solve this, we propose an instanc... | [
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25 | CompNVS: Novel View Synthesis with Scene Completion | [
"Zuoyue Li",
"Tianxing Fan",
"Zhenqiang Li",
"Zhaopeng Cui",
"Yoichi Sato",
"Marc Pollefeys",
"Martin R. Oswald"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/2786_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610441.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610441-supp.pdf | 10.1007/978-3-031-19769-7_26 | 2207.11467 | title_snapshot | We introduce a scalable framework for novel view synthesis from RGB-D images with largely incomplete scene coverage. While generative neural approaches have demonstrated spectacular results on 2D images, they have not yet achieved similar photorealistic results in combination with scene completion where a spatial 3D sc... | [
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26 | SketchSampler: Sketch-Based 3D Reconstruction via View-Dependent Depth Sampling | [
"Chenjian Gao",
"Qian Yu",
"Lu Sheng",
"Yi-Zhe Song",
"Dong Xu"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/2822_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610457.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610457-supp.pdf | 10.1007/978-3-031-19769-7_27 | 2208.06880 | title_snapshot | Reconstructing a 3D shape based on a single sketch image is challenging due to the large domain gap between a sparse, irregular sketch and a regular, dense 3D shape. Existing works try to employ the global feature extracted from sketch to directly predict the 3D coordinates, but they usually suffer from losing fine det... | [
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27 | LocalBins: Improving Depth Estimation by Learning Local Distributions | [
"Shariq Farooq Bhat",
"Ibraheem Alhashim",
"Peter Wonka"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/2871_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610473.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610473-supp.pdf | 10.1007/978-3-031-19769-7_28 | 2203.15132 | title_snapshot | We propose a novel architecture for depth estimation from a single image. The architecture itself is based on the popular encoder-decoder architecture that is frequently used as a starting point for all dense regression tasks. We build on AdaBins which estimates a global distribution of depth values for the input image... | [
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28 | 2D GANs Meet Unsupervised Single-View 3D Reconstruction | [
"Feng Liu",
"Xiaoming Liu"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/2888_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610490.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610490-supp.pdf | 10.1007/978-3-031-19769-7_29 | 2207.10183 | title_snapshot | Recent research has shown that controllable image generation based on pre-trained GANs can benefit a wide range of computer vision tasks. However, less attention has been devoted to 3D vision tasks. In light of this, we propose a novel image-conditioned neural implicit field, which can leverage 2D supervisions from GAN... | [
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29 | InfiniteNature-Zero: Learning Perpetual View Generation of Natural Scenes from Single Images | [
"Zhengqi Li",
"Qianqian Wang",
"Noah Snavely",
"Angjoo Kanazawa"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/2911_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610508.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610508-supp.pdf | 10.1007/978-3-031-19769-7_30 | 2207.11148 | title_snapshot | We present a method for learning to generate unbounded flythrough videos of natural scenes starting from a single view. This capability is learned from a collection of single photographs, without requiring camera poses or even multiple views of each scene. To achieve this, we propose a novel self-supervised view genera... | [
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30 | Semi-Supervised Single-View 3D Reconstruction via Prototype Shape Priors | [
"Zhen Xing",
"Hengduo Li",
"Zuxuan Wu",
"Yu-Gang Jiang"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/3139_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610528.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610528-supp.pdf | 10.1007/978-3-031-19769-7_31 | 2209.15383 | title_snapshot | The performance of existing single-view 3D reconstruction methods heavily relies on large-scale of 3D annotations. However, such annotations are tedious and expensive to collect. Semi-supervised learning serves as an alternative way to mitigate the need for manual labels, but remains unexplored in 3D reconstruction. In... | [
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31 | Bilateral Normal Integration | [
"Xu Cao",
"Hiroaki Santo",
"Boxin Shi",
"Fumio Okura",
"Yasuyuki Matsushita"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/3202_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610545.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610545-supp.pdf | 10.1007/978-3-031-19769-7_32 | null | null | This paper studies the discontinuity preservation problem in recovering a surface from its surface normal map. To model discontinuities, we introduce the assumption that the surface to be recovered is semi-smooth, i.e., the surface is one-sided differentiable (hence one-sided continuous) everywhere in the horizontal an... | [
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32 | S2Contact: Graph-Based Network for 3D Hand-Object Contact Estimation with Semi-Supervised Learning | [
"Tze Ho Elden Tse",
"Zhongqun Zhang",
"Kwang In Kim",
"Aleš Leonardis",
"Feng Zheng",
"Hyung Jin Chang"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/3351_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610561.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610561-supp.pdf | 10.1007/978-3-031-19769-7_33 | 2208.00874 | title_judge | Being able to reason about the physical contacts between hands and objects is crucial in understanding hand-object manipulation. However, despite the efforts in accurate 3D annotations in hand and object datasets, there still exist gaps in 3D hand and object reconstructions. Recent works leverage contact maps to refine... | [
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33 | SC-wLS: Towards Interpretable Feed-Forward Camera Re-localization | [
"Xin Wu",
"Hao Zhao",
"Shunkai Li",
"Yingdian Cao",
"Hongbin Zha"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/3498_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610578.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610578-supp.pdf | 10.1007/978-3-031-19769-7_34 | 2210.12748 | title_snapshot | Visual re-localization aims to recover camera poses in a known environment, which is vital for applications like robotics or augmented reality. Feed-forward absolute camera pose regression methods directly output poses by a network, but suffer from low accuracy. Meanwhile, scene coordinate based methods are accurate, b... | [
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34 | FloatingFusion: Depth from ToF and Image-Stabilized Stereo Cameras | [
"Andreas Meuleman",
"Hakyeong Kim",
"James Tompkin",
"Min H. Kim"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/3503_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610595.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610595-supp.pdf | 10.1007/978-3-031-19769-7_35 | 2210.02785 | title_snapshot | High-accuracy per-pixel depth is vital for computational photography, so smartphones now have multimodal camera systems with time-of-flight (ToF) depth sensors and multiple color cameras. However, producing accurate high-resolution depth is still challenging due to the low resolution and limited active illumination pow... | [
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35 | DELTAR: Depth Estimation from a Light-Weight ToF Sensor and RGB Image | [
"Yijin Li",
"Xinyang Liu",
"Wenqi Dong",
"Han Zhou",
"Hujun Bao",
"Guofeng Zhang",
"Yinda Zhang",
"Zhaopeng Cui"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/3514_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610612.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610612-supp.zip | 10.1007/978-3-031-19769-7_36 | 2209.13362 | title_snapshot | Light-weight time-of-flight (ToF) depth sensors are small, cheap, low-energy and have been massively deployed on mobile devices for the purposes like autofocus, obstacle detection, etc. However, due to their specific measurements (depth distribution in a region instead of the depth value at a certain pixel) and extreme... | [
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36 | 3D Room Layout Estimation from a Cubemap of Panorama Image via Deep Manhattan Hough Transform | [
"Yining Zhao",
"Chao Wen",
"Zhou Xue",
"Yue Gao"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/3606_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610630.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610630-supp.pdf | 10.1007/978-3-031-19769-7_37 | 2207.09291 | title_snapshot | Significant geometric structures can be compactly described by global wireframes in the estimation of 3D room layout from a single panoramic image. Based on this observation, we present an alternative approach to estimate the walls in 3D space by modeling long-range geometric patterns in a learnable Hough Transform blo... | [
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37 | RBP-Pose: Residual Bounding Box Projection for Category-Level Pose Estimation | [
"Ruida Zhang",
"Yan Di",
"Zhiqiang Lou",
"Fabian Manhardt",
"Federico Tombari",
"Xiangyang Ji"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/3809_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610647.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610647-supp.pdf | 10.1007/978-3-031-19769-7_38 | 2208.00237 | title_snapshot | Category-level object pose estimation aims to predict the 6D pose as well as the 3D metric size of previously unseen objects from a known set of categories. Recent methods harness shape prior adaptation to map the observed point cloud into the canonical space and apply Umeyama’s algorithm to recover the pose and size. ... | [
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38 | Monocular 3D Object Reconstruction with GAN Inversion | [
"Junzhe Zhang",
"Daxuan Ren",
"Zhongang Cai",
"Chai Kiat Yeo",
"Bo Dai",
"Chen Change Loy"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/3999_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610665.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610665-supp.pdf | 10.1007/978-3-031-19769-7_39 | 2207.10061 | title_snapshot | Recovering a textured 3D mesh from a monocular image is highly challenging, particularly for in-the-wild objects that lack 3D ground truths. In this work, we present MeshInversion, a novel framework to improve the reconstruction by exploiting the generative prior of a 3D GAN pre-trained for 3D textured mesh synthesis. ... | [
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39 | Map-Free Visual Relocalization: Metric Pose Relative to a Single Image | [
"Eduardo Arnold",
"Jamie Wynn",
"Sara Vicente",
"Guillermo Garcia-Hernando",
"Aron Monszpart",
"Victor Prisacariu",
"Daniyar Turmukhambetov",
"Eric Brachmann"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/4029_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610682.pdf | null | 10.1007/978-3-031-19769-7_40 | 2210.05494 | title_snapshot | Can we relocalize in a scene represented by a single reference image? Standard visual relocalization requires hundreds of images and scale calibration to build a scene-specific 3D map. In contrast, we propose Map-free Relocalization, i.e., using only one photo of a scene to enable instant, metric scaled relocalization.... | [
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40 | Self-Distilled Feature Aggregation for Self-Supervised Monocular Depth Estimation | [
"Zhengming Zhou",
"Qiulei Dong"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/4073_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610700.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610700-supp.pdf | 10.1007/978-3-031-19769-7_41 | 2209.07088 | title_snapshot | Self-supervised monocular depth estimation has received much attention recently in computer vision. Most of the existing works in literature aggregate multi-scale features for depth prediction via either straightforward concatenation or element-wise addition, however, such feature aggregation operations generally negle... | [
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41 | Planes vs. Chairs: Category-Guided 3D Shape Learning without Any 3D Cues | [
"Zixuan Huang",
"Stefan Stojanov",
"Anh Thai",
"Varun Jampani",
"James M. Rehg"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/4231_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610717.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136610717-supp.pdf | 10.1007/978-3-031-19769-7_42 | 2204.10235 | title_snapshot | We present a novel 3D shape reconstruction method which learns to predict an implicit 3D shape representation from a single RGB image. Our approach uses a set of single-view images of multiple object categories without viewpoint annotation, forcing the model to learn across multiple object categories without 3D supervi... | [
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42 | MHR-Net: Multiple-Hypothesis Reconstruction of Non-rigid Shapes from 2D Views | [
"Haitian Zeng",
"Xin Yu",
"Jiaxu Miao",
"Yi Yang"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/4241_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620001.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620001-supp.pdf | 10.1007/978-3-031-20086-1_1 | 2207.09086 | title_snapshot | We propose MHR-Net, a novel method for recovering Non-Rigid Shapes from Motion (NRSfM). MHR-Net aims to find a set of reasonable reconstructions for a 2D view, and it also selects the most likely reconstruction from the set. To deal with the challenging unsupervised generation of non-rigid shapes, we develop a new Dete... | [
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43 | Depth Map Decomposition for Monocular Depth Estimation | [
"Jinyoung Jun",
"Jae-Han Lee",
"Chul Lee",
"Chang-Su Kim"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/4247_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620018.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620018-supp.pdf | 10.1007/978-3-031-20086-1_2 | 2208.10762 | title_snapshot | We propose a novel algorithm for monocular depth estimation that decomposes a metric depth map into a normalized depth map and scale features. The proposed network is composed of a shared encoder and three decoders, called G-Net, N-Net, and M-Net, which estimate gradient maps, a normalized depth map, and a metric depth... | [
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44 | Monitored Distillation for Positive Congruent Depth Completion | [
"Tian Yu Liu",
"Parth Agrawal",
"Allison Chen",
"Byung-Woo Hong",
"Alex Wong"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/4288_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620035.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620035-supp.pdf | 10.1007/978-3-031-20086-1_3 | 2203.16034 | title_snapshot | We propose a method to infer a dense depth map from a single image, its calibration, and the associated sparse point cloud. In order to leverage existing models (teachers) that produce putative depth maps, we propose an adaptive knowledge distillation approach that yields a positive congruent training process, wherein ... | [
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45 | Resolution-Free Point Cloud Sampling Network with Data Distillation | [
"Tianxin Huang",
"Jiangning Zhang",
"Jun Chen",
"Yuang Liu",
"Yong Liu"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/4326_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620053.pdf | null | 10.1007/978-3-031-20086-1_4 | null | null | Down-sampling algorithms are adopted to simplify the point clouds and save the computation cost on subsequent tasks. Existing learning-based sampling methods often need to train a big sampling network to support sampling under different resolutions, which must generate sampled points with the costly maximum resolution ... | [
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46 | Organic Priors in Non-rigid Structure from Motion | [
"Suryansh Kumar",
"Luc Van Gool"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/4720_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620069.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620069-supp.pdf | 10.1007/978-3-031-20086-1_5 | 2207.06262 | title_snapshot | This paper advocates the use of organic priors in classical non-rigid structure from motion (NRSfM). By organic priors, we mean invaluable intermediate prior information intrinsic to the NRSfM matrix factorization theory. It is shown that such priors reside in the factorized matrices, and quite surprisingly, existing m... | [
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47 | Perspective Flow Aggregation for Data-Limited 6D Object Pose Estimation | [
"Yinlin Hu",
"Pascal Fua",
"Mathieu Salzmann"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/4807_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620087.pdf | null | 10.1007/978-3-031-20086-1_6 | 2203.09836 | title_snapshot | Most recent 6D object pose estimation methods, including unsupervised ones, require many real training images. Unfortunately, for some applications, such as those in space or deep under water, acquiring real images, even unannotated, is virtually impossible. In this paper, we propose a method that can be trained solely... | [
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48 | DANBO: Disentangled Articulated Neural Body Representations via Graph Neural Networks | [
"Shih-Yang Su",
"Timur Bagautdinov",
"Helge Rhodin"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/4883_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620104.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620104-supp.pdf | 10.1007/978-3-031-20086-1_7 | 2205.01666 | title_snapshot | Deep learning greatly improved the realism of animatable human models by learning geometry and appearance from collections of 3D scans, template meshes, and multi-view imagery. High-resolution models enable photo-realistic avatars but at the cost of requiring studio settings not available to end users. Our goal is to c... | [
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49 | "CHORE: Contact, Human and Object REconstruction from a Single RGB Image" | [
"Xianghui Xie",
"Bharat Lal Bhatnagar",
"Gerard Pons-Moll"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/4894_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620121.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620121-supp.pdf | 10.1007/978-3-031-20086-1_8 | 2204.02445 | title_snapshot | Most prior works in perceiving 3D humans from images reason human in isolation without their surroundings. However, humans are constantly interacting with the surrounding objects, thus calling for models that can reason about not only the human but also the object and their interaction. The problem is extremely challen... | [
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50 | Learned Vertex Descent: A New Direction for 3D Human Model Fitting | [
"Enric Corona",
"Gerard Pons-Moll",
"Guillem Alenyà",
"Francesc Moreno-Noguer"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/4918_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620141.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620141-supp.pdf | 10.1007/978-3-031-20086-1_9 | 2205.06254 | title_snapshot | We propose a novel optimization-based paradigm for 3D human shape fitting on images. In contrast to existing approaches that directly regress the parameters of a low-dimensional statistical body model (e.g. SMPL) from input images, we propose training a deep network that, given solely image features and an unfit mesh, ... | [
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51 | Self-Calibrating Photometric Stereo by Neural Inverse Rendering | [
"Junxuan Li",
"Hongdong Li"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/5007_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620160.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620160-supp.pdf | 10.1007/978-3-031-20086-1_10 | 2207.07815 | title_snapshot | This paper tackles the task of uncalibrated photometric stereo for 3D object reconstruction, where both the object shape, object reflectance, and lighting directions are unknown. This is an extremely difficult task, and the challenge is further compounded with the existence of the well-known generalized bas-relief (GBR... | [
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52 | 3D Clothed Human Reconstruction in the Wild | [
"Gyeongsik Moon",
"Hyeongjin Nam",
"Takaaki Shiratori",
"Kyoung Mu Lee"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/5036_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620177.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620177-supp.pdf | 10.1007/978-3-031-20086-1_11 | 2207.10053 | title_snapshot | Although much progress has been made in 3D clothed human reconstruction, most of the existing methods fail to produce robust results from in-the-wild images, which contain diverse human poses and appearances. This is mainly due to the large domain gap between training datasets and in-the-wild datasets. The training dat... | [
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53 | Directed Ray Distance Functions for 3D Scene Reconstruction | [
"Nilesh Kulkarni",
"Justin Johnson",
"David F. Fouhey"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/5180_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620193.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620193-supp.pdf | 10.1007/978-3-031-20086-1_12 | 2112.04481 | title_judge | We present an approach for full 3D scene reconstruction from a single new image that can be trained on realistic non-watertight scans. Our approach uses a predicted distance function, since these have shown promise in handling complex topologies and large spaces. We identify and analyze two key challenges for predictin... | [
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54 | Object Level Depth Reconstruction for Category Level 6D Object Pose Estimation from Monocular RGB Image | [
"Zhaoxin Fan",
"Zhenbo Song",
"Jian Xu",
"Zhicheng Wang",
"Kejian Wu",
"Hongyan Liu",
"Jun He"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/5287_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620212.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620212-supp.pdf | 10.1007/978-3-031-20086-1_13 | 2204.01586 | title_snapshot | Recently, RGBD-based category-level 6D object pose estimation has achieved promising improvement in performance, however, the requirement of depth information prohibits broader applications. In order to relieve this problem, this paper proposes a novel approach named Object Level Depth reconstruction Network (OLD-Net) ... | [
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55 | Uncertainty Quantification in Depth Estimation via Constrained Ordinal Regression | [
"Dongting Hu",
"Liuhua Peng",
"Tingjin Chu",
"Xiaoxing Zhang",
"Yinian Mao",
"Howard Bondell",
"Mingming Gong"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/5351_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620229.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620229-supp.pdf | 10.1007/978-3-031-20086-1_14 | null | null | Monocular Depth Estimation (MDE) is a task to predict a dense depth map from a single image. Despite the recent progress brought by deep learning, existing methods are still prone to errors due to the ill-posed nature of MDE. Hence depth estimation systems must be self-aware of possible mistakes to avoid disastrous con... | [
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56 | CostDCNet: Cost Volume Based Depth Completion for a Single RGB-D Image | [
"Jaewon Kam",
"Jungeon Kim",
"Soongjin Kim",
"Jaesik Park",
"Seungyong Lee"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/5688_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620248.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620248-supp.pdf | 10.1007/978-3-031-20086-1_15 | null | null | Successful depth completion from a single RGB-D image requires both extracting plentiful 2D and 3D features and merging these heterogeneous features appropriately. We propose a novel depth completion framework, CostDCNet, based on the cost volume-based depth estimation approach that has been successfully employed for m... | [
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57 | "ShAPO: Implicit Representations for Multi-Object Shape, Appearance, and Pose Optimization" | [
"Muhammad Zubair Irshad",
"Sergey Zakharov",
"Rareș Ambruș",
"Thomas Kollar",
"Zsolt Kira",
"Adrien Gaidon"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/5770_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620266.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620266-supp.zip | 10.1007/978-3-031-20086-1_16 | 2207.13691 | title_snapshot | Our method studies the complex task of object-centric 3D understanding from a single RGB-D observation. As it is an ill-posed problem, existing methods suffer from low performance for both 3D shape and 6D pose and size estimation in complex multi-object scenarios with occlusions. We present ShAPO, a method for joint mu... | [
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58 | 3D Siamese Transformer Network for Single Object Tracking on Point Clouds | [
"Le Hui",
"Lingpeng Wang",
"Linghua Tang",
"Kaihao Lan",
"Jin Xie",
"Jian Yang"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/5829_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620284.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620284-supp.pdf | 10.1007/978-3-031-20086-1_17 | 2207.11995 | title_snapshot | Siamese network based trackers formulate 3D single object tracking as cross-correlation learning between point features of a template and a search area. Due to the large appearance variation between the template and search area during tracking, how to learn the robust cross correlation between them for identifying the ... | [
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59 | Object Wake-Up: 3D Object Rigging from a Single Image | [
"Ji Yang",
"Xinxin Zuo",
"Sen Wang",
"Zhenbo Yu",
"Xingyu Li",
"Bingbing Ni",
"Minglun Gong",
"Li Cheng"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/5901_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620302.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620302-supp.pdf | 10.1007/978-3-031-20086-1_18 | 2108.02708 | title_snapshot | Given a single chair image, could we wake it up by reconstructing its 3D shape and skeleton, as well as animating its plausible articulations and motions, similar to that of human modeling? It is a new problem that not only goes beyond image-based object reconstruction but also involves articulated animation of generic... | [
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60 | IntegratedPIFu: Integrated Pixel Aligned Implicit Function for Single-View Human Reconstruction | [
"Kennard Yanting Chan",
"Guosheng Lin",
"Haiyu Zhao",
"Weisi Lin"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/5915_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620319.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620319-supp.pdf | 10.1007/978-3-031-20086-1_19 | 2211.07955 | title_snapshot | We propose IntegratedPIFu, a new pixel-aligned implicit model that builds on the foundation set by PIFuHD. IntegratedPIFu shows how depth and human parsing information can be predicted and capitalized upon in a pixel-aligned implicit model. In addition, IntegratedPIFu introduces depth-oriented sampling, a novel trainin... | [
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61 | Realistic One-Shot Mesh-Based Head Avatars | [
"Taras Khakhulin",
"Vanessa Sklyarova",
"Victor Lempitsky",
"Egor Zakharov"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/6023_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620336.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620336-supp.pdf | 10.1007/978-3-031-20086-1_20 | 2206.08343 | title_snapshot | We present a system for the creation of realistic one-shot mesh-based (ROME) human head avatars. From a single photograph, our system estimates the head mesh (with person-specific details in both the facial and non-facial head parts) as well as the neural texture encoding local photometric and geometric details. The re... | [
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62 | A Kendall Shape Space Approach to 3D Shape Estimation from 2D Landmarks | [
"Martha Paskin",
"Daniel Baum",
"Mason N. Dean",
"Christoph von Tycowicz"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/6090_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620354.pdf | null | 10.1007/978-3-031-20086-1_21 | 2207.12687 | title_snapshot | 3D shapes provide substantially more information than 2D images. However, the acquisition of 3D shapes is sometimes very difficult or even impossible in comparison with acquiring 2D images, making it necessary to derive the 3D shape from 2D images. Although this is, in general, a mathematically ill-posed problem, it mi... | [
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63 | Neural Light Field Estimation for Street Scenes with Differentiable Virtual Object Insertion | [
"Zian Wang",
"Wenzheng Chen",
"David Acuna",
"Jan Kautz",
"Sanja Fidler"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/6516_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620370.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620370-supp.pdf | 10.1007/978-3-031-20086-1_22 | 2208.09480 | title_snapshot | We consider the challenging problem of outdoor lighting estimation for the goal of photorealistic virtual object insertion into photographs. Existing works on outdoor lighting estimation typically simplify the scene lighting into an environment map which cannot capture the spatially-varying lighting effects in outdoor ... | [
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64 | Perspective Phase Angle Model for Polarimetric 3D Reconstruction | [
"Guangcheng Chen",
"Li He",
"Yisheng Guan",
"Hong Zhang"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/6667_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620387.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620387-supp.zip | 10.1007/978-3-031-20086-1_23 | 2207.09629 | title_snapshot | Current polarimetric 3D reconstruction methods, including those in the well-established shape from polarization literature, are all developed under the orthographic projection assumption. In the case of a large field of view, however, this assumption does not hold and may result in significant reconstruction errors in ... | [
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65 | DeepShadow: Neural Shape from Shadow | [
"Asaf Karnieli",
"Ohad Fried",
"Yacov Hel-Or"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/7476_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620403.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620403-supp.pdf | 10.1007/978-3-031-20086-1_24 | 2203.15065 | title_snapshot | This paper presents ‘DeepShadow’, a one-shot method for recovering the depth map and surface normals from photometric stereo shadow maps. Previous works that try to recover the surface normals from photometric stereo images treat cast shadows as a disturbance. We show that the self and cast shadows not only do not dist... | [
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66 | Camera Auto-Calibration from the Steiner Conic of the Fundamental Matrix | [
"Yu Liu",
"Hui Zhang"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/7605_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620419.pdf | null | 10.1007/978-3-031-20086-1_25 | null | null | This paper addresses the problem of camera auto-calibration from the fundamental matrix under general motion. The fundamental matrix can be decomposed into a symmetric part (a Steiner conic) and a skew-symmetric part (a fixed point), which we find useful for fully calibrating camera parameters. We first obtain a fixed ... | [
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67 | Super-Resolution 3D Human Shape from a Single Low-Resolution Image | [
"Marco Pesavento",
"Marco Volino",
"Adrian Hilton"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/7765_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620435.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620435-supp.pdf | 10.1007/978-3-031-20086-1_26 | 2208.10738 | title_snapshot | We propose a novel framework to reconstruct super-resolution human shape from a single low-resolution input image. The approach overcomes limitations of existing approaches that reconstruct 3D human shape from a single image, which require high-resolution images together with auxiliary data such as surface normal or a ... | [
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68 | Minimal Neural Atlas: Parameterizing Complex Surfaces with Minimal Charts and Distortion | [
"Weng Fei Low",
"Gim Hee Lee"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/107_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620452.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620452-supp.pdf | 10.1007/978-3-031-20086-1_27 | 2207.14782 | title_snapshot | Explicit neural surface representations allow for exact and efficient extraction of the encoded surface at arbitrary precision, as well as analytic derivation of differential geometric properties such as surface normal and curvature. Such desirable properties, which are absent in its implicit counterpart, makes it idea... | [
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69 | ExtrudeNet: Unsupervised Inverse Sketch-and-Extrude for Shape Parsing | [
"Daxuan Ren",
"Jianmin Zheng",
"Jianfei Cai",
"Jiatong Li",
"Junzhe Zhang"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/194_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620468.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620468-supp.pdf | 10.1007/978-3-031-20086-1_28 | 2209.15632 | title_snapshot | Sketch-and-extrude is a common and intuitive modeling process in computer aided design. This paper studies the problem of learning the shape given in the form of point clouds by “inverse” sketch-and-extrude. We present ExtrudeNet, an unsupervised end-to-end network for discovering sketch and extrude from point clouds. ... | [
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70 | CATRE: Iterative Point Clouds Alignment for Category-Level Object Pose Refinement | [
"Xingyu Liu",
"Gu Wang",
"Yi Li",
"Xiangyang Ji"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/326_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620485.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620485-supp.pdf | 10.1007/978-3-031-20086-1_29 | 2207.08082 | title_snapshot | While category-level 9DoF object pose estimation has emerged recently, previous correspondence-based or direct regression methods are both limited in accuracy due to the huge intra-category variances in object shape and color, etc. Orthogonal to them, this work presents a category-level object pose and size refiner CAT... | [
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71 | Optimization over Disentangled Encoding: Unsupervised Cross-Domain Point Cloud Completion via Occlusion Factor Manipulation | [
"Jingyu Gong",
"Fengqi Liu",
"Jiachen Xu",
"Min Wang",
"Xin Tan",
"Zhizhong Zhang",
"Ran Yi",
"Haichuan Song",
"Yuan Xie",
"Lizhuang Ma"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/361_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620504.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620504-supp.zip | 10.1007/978-3-031-20086-1_30 | null | null | Recently, studies considering domain gaps in shape completion attracted more attention, due to the undesirable performance of supervised methods on real scans. They only noticed the gap in input scans, but ignored the gap in output prediction, which is specific for completion. In this paper, we disentangle partial scan... | [
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72 | Unsupervised Learning of 3D Semantic Keypoints with Mutual Reconstruction | [
"Haocheng Yuan",
"Chen Zhao",
"Shichao Fan",
"Jiaxi Jiang",
"Jiaqi Yang"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/463_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620521.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620521-supp.pdf | 10.1007/978-3-031-20086-1_31 | 2203.10212 | title_snapshot | Semantic 3D keypoints are category-level semantic consistent points on 3D objects. Detecting 3D semantic keypoints is a foundation for a number of 3D vision tasks but remains challenging, due to the ambiguity of semantic information, especially when the objects are represented by unordered 3D point clouds. Existing uns... | [
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73 | MvDeCor: Multi-View Dense Correspondence Learning for Fine-Grained 3D Segmentation | [
"Gopal Sharma",
"Kangxue Yin",
"Subhransu Maji",
"Evangelos Kalogerakis",
"Or Litany",
"Sanja Fidler"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/525_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620538.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620538-supp.pdf | 10.1007/978-3-031-20086-1_32 | 2208.08580 | title_snapshot | We propose to utilize self-supervised techniques in the 2D domain for fine-grained 3D shape segmentation tasks. This is inspired by the observation that view-based surface representations are more effective at modeling high-resolution surface details and texture than their 3D counterparts based on point clouds or voxel... | [
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74 | SUPR: A Sparse Unified Part-Based Human Representation | [
"Ahmed A. A. Osman",
"Timo Bolkart",
"Dimitrios Tzionas",
"Michael J. Black"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/570_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620555.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620555-supp.pdf | 10.1007/978-3-031-20086-1_33 | 2210.13861 | title_snapshot | Statistical 3D shape models of the head, hands, and full body are widely used in computer vision and graphics. Despite their wide use, we show that existing models of the head and hands fail to capture the full range of motion for these parts. Moreover, existing work largely ignores the feet, which are crucial for mode... | [
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75 | Revisiting Point Cloud Simplification: A Learnable Feature Preserving Approach | [
"Rolandos Alexandros Potamias",
"Giorgos Bouritsas",
"Stefanos Zafeiriou"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/584_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620573.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620573-supp.pdf | 10.1007/978-3-031-20086-1_34 | 2109.14982 | title_snapshot | The recent advances in 3D sensing technology have made possible the capture of point clouds in significantly high resolution. However, increased detail usually comes at the expense of high storage, as well as computational costs in terms of processing and visualization operations. Mesh and Point Cloud simplification me... | [
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76 | Masked Autoencoders for Point Cloud Self-Supervised Learning | [
"Yatian Pang",
"Wenxiao Wang",
"Francis E.H. Tay",
"Wei Liu",
"Yonghong Tian",
"Li Yuan"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/800_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620591.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620591-supp.pdf | 10.1007/978-3-031-20086-1_35 | 2203.06604 | title_snapshot | As a promising scheme of self-supervised learning, masked autoencoding has significantly advanced natural language processing and computer vision. Inspired by this, we propose a neat scheme of masked autoencoders for point cloud self-supervised learning, addressing the challenges posed by point cloud’s properties, incl... | [
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77 | Intrinsic Neural Fields: Learning Functions on Manifolds | [
"Lukas Koestler",
"Daniel Grittner",
"Michael Moeller",
"Daniel Cremers",
"Zorah Lähner"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/927_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620609.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620609-supp.zip | 10.1007/978-3-031-20086-1_36 | 2203.07967 | title_snapshot | Neural fields have gained significant attention in the computer vision community due to their excellent performance in novel view synthesis, geometry reconstruction, and generative modeling. Some of their advantages are a sound theoretic foundation and an easy implementation in current deep learning frameworks. While n... | [
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78 | Skeleton-Free Pose Transfer for Stylized 3D Characters | [
"Zhouyingcheng Liao",
"Jimei Yang",
"Jun Saito",
"Gerard Pons-Moll",
"Yang Zhou"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/1103_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620627.pdf | null | 10.1007/978-3-031-20086-1_37 | 2208.00790 | title_snapshot | We present the first method that automatically transfers poses between stylized 3D characters without skeletal rigging. In contrast to previous attempts to learn pose transformations on fixed or topology-equivalent skeleton templates, our method focuses on a novel scenario to handle skeleton-free characters with divers... | [
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79 | Masked Discrimination for Self-Supervised Learning on Point Clouds | [
"Haotian Liu",
"Mu Cai",
"Yong Jae Lee"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/1209_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620645.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620645-supp.pdf | 10.1007/978-3-031-20086-1_38 | 2203.11183 | title_snapshot | Masked autoencoding has achieved great success for self-supervised learning in the image and language domains. However, mask based pretraining has yet to show benefits for point cloud understanding, likely due to standard backbones like PointNet being unable to properly handle the training versus testing distribution m... | [
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80 | FBNet: Feedback Network for Point Cloud Completion | [
"Xuejun Yan",
"Hongyu Yan",
"Jingjing Wang",
"Hang Du",
"Zhihong Wu",
"Di Xie",
"Shiliang Pu",
"Li Lu"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/1272_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620664.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620664-supp.pdf | 10.1007/978-3-031-20086-1_39 | 2210.03974 | title_snapshot | The rapid development of point cloud learning has driven point cloud completion into a new era. However, the information flows of most existing completion methods are solely feedforward, and high-level information is rarely reused to improve low-level feature learning. To this end, we propose a novel Feedback Network (... | [
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81 | Meta-Sampler: Almost-Universal yet Task-Oriented Sampling for Point Clouds | [
"Ta-Ying Cheng",
"Qingyong Hu",
"Qian Xie",
"Niki Trigoni",
"Andrew Markham"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/1516_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620682.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620682-supp.pdf | 10.1007/978-3-031-20086-1_40 | 2203.16001 | title_snapshot | Sampling is a key operation in point-cloud task and acts to increase computational efficiency and tractability by discarding redundant points. Universal sampling algorithms (e.g., Farthest Point Sampling) work without modification across different tasks, models, and datasets, but by their very nature are agnostic about... | [
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82 | A Level Set Theory for Neural Implicit Evolution under Explicit Flows | [
"Ishit Mehta",
"Manmohan Chandraker",
"Ravi Ramamoorthi"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/1742_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620699.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620699-supp.pdf | 10.1007/978-3-031-20086-1_41 | 2204.07159 | title_snapshot | Coordinate-based neural networks parameterizing implicit surfaces have emerged as efficient representations of geometry. They effectively act as parametric level sets with the zero-level set defining the surface of interest. We present a framework that allows applying deformation operations defined for triangle meshes ... | [
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83 | Efficient Point Cloud Analysis Using Hilbert Curve | [
"Wanli Chen",
"Xinge Zhu",
"Guojin Chen",
"Bei Yu"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/1859_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620717.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620717-supp.pdf | 10.1007/978-3-031-20086-1_42 | null | null | Previous state-of-the-art research on analyzing point cloud mainly rely on the voxelization quantization because it keeps the better spatial locality and geometry. However, these 3D voxelization methods and subsequent 3D convolution networks often bring the large computational overhead and GPU occupation. A straightfor... | [
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84 | TOCH: Spatio-Temporal Object-to-Hand Correspondence for Motion Refinement | [
"Keyang Zhou",
"Bharat Lal Bhatnagar",
"Jan Eric Lenssen",
"Gerard Pons-Moll"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/1991_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136630001.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136630001-supp.zip | 10.1007/978-3-031-20062-5_1 | 2205.07982 | title_snapshot | We present TOCH, a method for refining incorrect 3D hand-object interaction sequences using a data prior. Existing hand trackers, especially those that rely on very few cameras, often produce visually unrealistic results with hand-object intersection or missing contacts. Although correcting such errors requires reasoni... | [
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85 | LaTeRF: Label and Text Driven Object Radiance Fields | [
"Ashkan Mirzaei",
"Yash Kant",
"Jonathan Kelly",
"Igor Gilitschenski"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/2145_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136630021.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136630021-supp.pdf | 10.1007/978-3-031-20062-5_2 | 2207.01583 | title_snapshot | Obtaining 3D object representations is important for creating photo-realistic simulators and collecting assets for AR/VR applications. Neural fields have shown their effectiveness in learning a continuous volumetric representation of a scene from 2D images, but acquiring object representations from these models with we... | [
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86 | MeshMAE: Masked Autoencoders for 3D Mesh Data Analysis | [
"Yaqian Liang",
"Shanshan Zhao",
"Baosheng Yu",
"Jing Zhang",
"Fazhi He"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/2319_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136630038.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136630038-supp.pdf | 10.1007/978-3-031-20062-5_3 | 2207.10228 | title_snapshot | Recently, self-supervised pre-training has advanced Vision Transformers on various tasks w.r.t. different data modalities, e.g., image and 3D point cloud data. In this paper, we explore this learning paradigm for 3D mesh data analysis based on Transformers. Since applying Transformer architectures to new modalities is ... | [
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87 | Unsupervised Deep Multi-Shape Matching | [
"Dongliang Cao",
"Florian Bernard"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/2459_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136630056.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136630056-supp.pdf | 10.1007/978-3-031-20062-5_4 | 2207.09610 | title_snapshot | 3D shape matching is a long-standing problem in computer vision and computer graphics. While deep neural networks were shown to lead to state-of-the-art results in shape matching, existing learning-based approaches are limited in the context of multi-shape matching: (i) either they focus on matching pairs of shapes onl... | [
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88 | Texturify: Generating Textures on 3D Shape Surfaces | [
"Yawar Siddiqui",
"Justus Thies",
"Fangchang Ma",
"Qi Shan",
"Matthias Nießner",
"Angela Dai"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/2573_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136630073.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136630073-supp.zip | 10.1007/978-3-031-20062-5_5 | 2204.02411 | title_snapshot | Texture cues on 3D objects are key to compelling visual representations, with the possibility to create high visual fidelity with inherent spatial consistency across different views. Since the availability of textured 3D shapes remains very limited, learning a 3D-supervised data-driven method that predicts a texture ba... | [
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89 | Autoregressive 3D Shape Generation via Canonical Mapping | [
"An-Chieh Cheng",
"Xueting Li",
"Sifei Liu",
"Min Sun",
"Ming-Hsuan Yang"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/2586_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136630091.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136630091-supp.pdf | 10.1007/978-3-031-20062-5_6 | 2204.01955 | title_snapshot | With the capacity of modeling long-range dependencies in sequential data, transformers have shown remarkable performances in a variety of generative tasks such as image, audio, and text generation. Yet, taming them in generating less structured and voluminous data formats such as high-resolution point clouds have seldo... | [
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90 | PointTree: Transformation-Robust Point Cloud Encoder with Relaxed K-D Trees | [
"Jun-Kun Chen",
"Yu-Xiong Wang"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/2625_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136630107.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136630107-supp.pdf | 10.1007/978-3-031-20062-5_7 | 2208.05962 | title_snapshot | Being able to learn an effective semantic representation directly on raw point clouds has become a central topic in 3D understanding. Despite rapid progress, state-of-the-art encoders are restrictive to canonicalized point clouds, and have weaker than necessary performance when encountering geometric transformation dis... | [
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91 | UNIF: United Neural Implicit Functions for Clothed Human Reconstruction and Animation | [
"Shenhan Qian",
"Jiale Xu",
"Ziwei Liu",
"Liqian Ma",
"Shenghua Gao"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/2902_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136630123.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136630123-supp.pdf | 10.1007/978-3-031-20062-5_8 | 2207.09835 | title_snapshot | We propose united implicit functions (UNIF), a part-based method for clothed human reconstruction and animation with raw scans and skeletons as the input. Previous part-based methods for human reconstruction rely on ground-truth part labels from SMPL and thus are limited to minimal-clothed humans. In contrast, our meth... | [
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92 | PRIF: Primary Ray-Based Implicit Function | [
"Brandon Y. Feng",
"Yinda Zhang",
"Danhang Tang",
"Ruofei Du",
"Amitabh Varshney"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/2921_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136630140.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136630140-supp.pdf | 10.1007/978-3-031-20062-5_9 | 2208.06143 | title_snapshot | We introduce a new implicit shape representation called Primary Ray-based Implicit Function (PRIF). In contrast to most existing approaches based on the signed distance function (SDF) which handles spatial locations, our representation operates on oriented rays. Specifically, PRIF is formulated to directly produce the ... | [
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93 | Point Cloud Domain Adaptation via Masked Local 3D Structure Prediction | [
"Hanxue Liang",
"Hehe Fan",
"Zhiwen Fan",
"Yi Wang",
"Tianlong Chen",
"Yu Cheng",
"Zhangyang Wang"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/3035_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136630159.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136630159-supp.pdf | 10.1007/978-3-031-20062-5_10 | null | null | The superiority of deep learning based point cloud representations relies on large-scale labeled datasets, while the annotation of point clouds is notoriously expensive. One of the most effective solutions is to transfer the knowledge from existing labeled source data to unlabeled target data. However, domain bias typi... | [
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94 | CLIP-Actor: Text-Driven Recommendation and Stylization for Animating Human Meshes | [
"Kim Youwang",
"Kim Ji-Yeon",
"Tae-Hyun Oh"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/3229_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136630176.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136630176-supp.pdf | 10.1007/978-3-031-20062-5_11 | 2206.04382 | title_snapshot | We propose CLIP-Actor, a text-driven motion recommendation and neural mesh stylization system for human mesh animation. CLIP-Actor animates a 3D human mesh to conform to a text prompt by recommending a motion sequence and optimizing mesh style attributes. We build a text-driven human motion recommendation system by lev... | [
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95 | PlaneFormers: From Sparse View Planes to 3D Reconstruction | [
"Samir Agarwala",
"Linyi Jin",
"Chris Rockwell",
"David F. Fouhey"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/3429_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136630194.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136630194-supp.pdf | 10.1007/978-3-031-20062-5_12 | 2208.04307 | title_snapshot | We present an approach for the planar surface reconstruction of a scene from images with limited overlap. This reconstruction task is challenging since it requires jointly reasoning about single image 3D reconstruction, correspondence between images, and the relative camera pose between images. Past work has proposed o... | [
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96 | Learning Implicit Templates for Point-Based Clothed Human Modeling | [
"Siyou Lin",
"Hongwen Zhang",
"Zerong Zheng",
"Ruizhi Shao",
"Yebin Liu"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/3747_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136630211.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136630211-supp.zip | 10.1007/978-3-031-20062-5_13 | 2207.06955 | title_snapshot | We present FITE, a First-Implicit-Then-Explicit framework for modeling human avatars in clothing. Our framework first learns implicit surface templates representing the coarse clothing topology, and then employs the templates to guide the generation of point sets which further capture pose-dependent clothing deformatio... | [
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97 | Exploring the Devil in Graph Spectral Domain for 3D Point Cloud Attacks | [
"Qianjiang Hu",
"Daizong Liu",
"Wei Hu"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/4378_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136630230.pdf | null | 10.1007/978-3-031-20062-5_14 | 2202.07261 | title_snapshot | With the maturity of depth sensors, point clouds have received increasing attention in various applications such as autonomous driving, robotics, surveillance, \etc., while deep point cloud learning models have shown to be vulnerable to adversarial attacks. Existing attack methods generally add/delete points or perform... | [
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98 | Structure-Aware Editable Morphable Model for 3D Facial Detail Animation and Manipulation | [
"Jingwang Ling",
"Zhibo Wang",
"Ming Lu",
"Quan Wang",
"Chen Qian",
"Feng Xu"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/4426_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136630248.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136630248-supp.zip | 10.1007/978-3-031-20062-5_15 | 2207.09019 | title_snapshot | Morphable models are essential for the statistical modeling of 3D faces. Previous works on morphable models mostly focus on large-scale facial geometry but ignore facial details. This paper augments morphable models in representing facial details by learning a Structure-aware Editable Morphable Model (SEMM). SEMM intro... | [
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0.... |
99 | MoFaNeRF: Morphable Facial Neural Radiance Field | [
"Yiyu Zhuang",
"Hao Zhu",
"Xusen Sun",
"Xun Cao"
] | https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/4505_ECCV_2022_paper.php | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136630267.pdf | https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136630267-supp.zip | 10.1007/978-3-031-20062-5_16 | 2112.02308 | title_snapshot | We propose a parametric model that maps free-view images into a vector space of coded facial shape, expression and appearance with a neural radiance field, namely Morphable Facial NeRF. Specifically, MoFaNeRF takes the coded facial shape, expression and appearance along with space coordinate and view direction as input... | [
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0.0055989231914281845,
-0.06410007923841476,
... |
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