暂无分享,去创建一个
Andrea Vedaldi | Natalia Neverova | Deva Ramanan | Hanbyul Joo | Minh Vo | Gengshan Yang | A. Vedaldi | D. Ramanan | Minh Vo | H. Joo | N. Neverova | Gengshan Yang
[1] Yaser Sheikh,et al. Spatiotemporal Bundle Adjustment for Dynamic 3D Human Reconstruction in the Wild , 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[2] Deva Ramanan,et al. NeRS: Neural Reflectance Surfaces for Sparse-view 3D Reconstruction in the Wild , 2021, NeurIPS.
[3] Minsu Cho,et al. Self-Calibrating Neural Radiance Fields , 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV).
[4] Jia Deng,et al. DROID-SLAM: Deep Visual SLAM for Monocular, Stereo, and RGB-D Cameras , 2021, NeurIPS.
[5] A. Vedaldi,et al. DOVE: Learning Deformable 3D Objects by Watching Videos , 2021, International Journal of Computer Vision.
[6] Jonathan T. Barron,et al. HyperNeRF , 2021, ACM Trans. Graph..
[7] Yaron Lipman,et al. Volume Rendering of Neural Implicit Surfaces , 2021, NeurIPS.
[8] Taku Komura,et al. NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction , 2021, ArXiv.
[9] Iasonas Kokkinos,et al. To The Point: Correspondence-driven monocular 3D category reconstruction , 2021, NeurIPS.
[10] Christian Theobalt,et al. Neural actor , 2021, ACM Trans. Graph..
[11] Andrea Vedaldi,et al. Discovering Relationships between Object Categories via Universal Canonical Maps , 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[12] Yasamin Jafarian,et al. Learning High Fidelity Depths of Dressed Humans by Watching Social Media Dance Videos , 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[13] Simon Lucey,et al. Neural Trajectory Fields for Dynamic Novel View Synthesis , 2021, ArXiv.
[14] Varun Jampani,et al. LASR: Learning Articulated Shape Reconstruction from a Monocular Video , 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[15] Hujun Bao,et al. Animatable Neural Radiance Fields for Modeling Dynamic Human Bodies , 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV).
[16] Antonio Torralba,et al. BARF: Bundle-Adjusting Neural Radiance Fields , 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV).
[17] Michael J. Black,et al. SNARF: Differentiable Forward Skinning for Animating Non-Rigid Neural Implicit Shapes , 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV).
[18] Stephen Lin,et al. Neural Articulated Radiance Field , 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV).
[19] Michael J. Black,et al. SCANimate: Weakly Supervised Learning of Skinned Clothed Avatar Networks , 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[20] Hao Su,et al. GNeRF: GAN-based Neural Radiance Field without Posed Camera , 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV).
[21] Edgar Sucar,et al. iMAP: Implicit Mapping and Positioning in Real-Time , 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV).
[22] V. Prisacariu,et al. NeRF-: Neural Radiance Fields Without Known Camera Parameters , 2021, ArXiv.
[23] Shubham Tulsiani,et al. Shelf-Supervised Mesh Prediction in the Wild , 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[24] Helge Rhodin,et al. A-NeRF: Articulated Neural Radiance Fields for Learning Human Shape, Appearance, and Pose , 2021, NeurIPS.
[25] Hujun Bao,et al. Neural Body: Implicit Neural Representations with Structured Latent Codes for Novel View Synthesis of Dynamic Humans , 2020, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[26] M. Zollhöfer,et al. Non-Rigid Neural Radiance Fields: Reconstruction and Novel View Synthesis of a Dynamic Scene From Monocular Video , 2020, 2021 IEEE/CVF International Conference on Computer Vision (ICCV).
[27] Francesc Moreno-Noguer,et al. D-NeRF: Neural Radiance Fields for Dynamic Scenes , 2020, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[28] Zhengqi Li,et al. Neural Scene Flow Fields for Space-Time View Synthesis of Dynamic Scenes , 2020, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[29] Jonathan T. Barron,et al. Nerfies: Deformable Neural Radiance Fields , 2020, 2021 IEEE/CVF International Conference on Computer Vision (ICCV).
[30] Jonathan T. Barron,et al. NeRF in the Wild: Neural Radiance Fields for Unconstrained Photo Collections , 2020, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[31] D. Ramanan,et al. ViSER: Video-Specific Surface Embeddings for Articulated 3D Shape Reconstruction , 2021, NeurIPS.
[32] Xueting Li,et al. Online Adaptation for Consistent Mesh Reconstruction in the Wild , 2020, NeurIPS.
[33] Andrea Vedaldi,et al. Continuous Surface Embeddings , 2020, NeurIPS.
[34] Kostas Daniilidis,et al. 3D Bird Reconstruction: a Dataset, Model, and Shape Recovery from a Single View , 2020, ECCV.
[35] C. Stoll,et al. TexMesh: Reconstructing Detailed Human Texture and Geometry from RGB-D Video , 2020, ECCV.
[36] Roberto Cipolla,et al. Who Left the Dogs Out? 3D Animal Reconstruction with Expectation Maximization in the Loop , 2020, ECCV.
[37] Abhinav Gupta,et al. Implicit Mesh Reconstruction from Unannotated Image Collections , 2020, ArXiv.
[38] Jonathan T. Barron,et al. Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains , 2020, NeurIPS.
[39] Abhinav Gupta,et al. Articulation-Aware Canonical Surface Mapping , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[40] Ronen Basri,et al. Multiview Neural Surface Reconstruction by Disentangling Geometry and Appearance , 2020, NeurIPS.
[41] Pratul P. Srinivasan,et al. NeRF , 2020, ECCV.
[42] Jan Kautz,et al. Self-supervised Single-view 3D Reconstruction via Semantic Consistency , 2020, ECCV.
[43] Ross B. Girshick,et al. PointRend: Image Segmentation As Rendering , 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[44] Michael J. Black,et al. VIBE: Video Inference for Human Body Pose and Shape Estimation , 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[45] Suryansh Kumar,et al. Non-Rigid Structure from Motion: Prior-Free Factorization Method Revisited , 2019, 2020 IEEE Winter Conference on Applications of Computer Vision (WACV).
[46] Christian Theobalt,et al. Neural Dense Non-Rigid Structure from Motion with Latent Space Constraints , 2020, ECCV.
[47] Song-Chun Zhu,et al. DenseRaC: Joint 3D Pose and Shape Estimation by Dense Render-and-Compare , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[48] Michael J. Black,et al. Three-D Safari: Learning to Estimate Zebra Pose, Shape, and Texture From Images “In the Wild” , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[49] Simon Lucey,et al. Deep Non-Rigid Structure From Motion , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[50] Thomas Brox,et al. What Do Single-View 3D Reconstruction Networks Learn? , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[51] Dimitrios Tzionas,et al. Expressive Body Capture: 3D Hands, Face, and Body From a Single Image , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[52] Yaser Sheikh,et al. Monocular Total Capture: Posing Face, Body, and Hands in the Wild , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[53] Alain Trouvé,et al. Interpolating between Optimal Transport and MMD using Sinkhorn Divergences , 2018, AISTATS.
[54] David Picard,et al. Human Pose Regression by Combining Indirect Part Detection and Contextual Information , 2017, Comput. Graph..
[55] Deva Ramanan,et al. Volumetric Correspondence Networks for Optical Flow , 2019, NeurIPS.
[56] Michael J. Black,et al. Lions and Tigers and Bears: Capturing Non-rigid, 3D, Articulated Shape from Images , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[57] Jitendra Malik,et al. Learning Category-Specific Mesh Reconstruction from Image Collections , 2018, ECCV.
[58] Yong Jae Lee,et al. Hide-and-Seek: Forcing a Network to be Meticulous for Weakly-Supervised Object and Action Localization , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[59] Alex Kendall,et al. End-to-End Learning of Geometry and Context for Deep Stereo Regression , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[60] Michael J. Black,et al. 3D Menagerie: Modeling the 3D Shape and Pose of Animals , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[61] Jan-Michael Frahm,et al. Pixelwise View Selection for Unstructured Multi-View Stereo , 2016, ECCV.
[62] Jan-Michael Frahm,et al. Structure-from-Motion Revisited , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[63] Alec Jacobson,et al. Skinning: real-time shape deformation , 2014, SIGGRAPH ASIA Courses.
[64] Aleix M. Martínez,et al. Non-rigid structure from motion with complementary rank-3 spaces , 2011, CVPR 2011.
[65] Kurt Keutzer,et al. Dense Point Trajectories by GPU-Accelerated Large Displacement Optical Flow , 2010, ECCV.
[66] Richard Szeliski,et al. Building Rome in a day , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[67] Wojciech Matusik,et al. Articulated mesh animation from multi-view silhouettes , 2008, ACM Trans. Graph..
[68] Richard Szeliski,et al. Modeling the World from Internet Photo Collections , 2008, International Journal of Computer Vision.
[69] Steven M. Seitz,et al. Photo tourism: exploring photo collections in 3D , 2006, ACM Trans. Graph..
[70] Seth J. Teller,et al. Particle Video: Long-Range Motion Estimation Using Point Trajectories , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[71] Henning Biermann,et al. Recovering non-rigid 3D shape from image streams , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).