Towards Precise Completion of Deformable Shapes

[1]  Umberto Castellani,et al.  FARM: Functional Automatic Registration Method for 3D Human Bodies , 2018, Comput. Graph. Forum.

[2]  Quan Z. Sheng,et al.  Nonrigid Point Set Registration With Robust Transformation Learning Under Manifold Regularization , 2019, IEEE Transactions on Neural Networks and Learning Systems.

[3]  Jianfei Cai,et al.  Skeleton-Aware 3D Human Shape Reconstruction From Point Clouds , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

[4]  Xingyu Liu,et al.  MeteorNet: Deep Learning on Dynamic 3D Point Cloud Sequences , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

[5]  Maks Ovsjanikov,et al.  Correspondence-Free Region Localization for Partial Shape Similarity via Hamiltonian Spectrum Alignment , 2019, 2019 International Conference on 3D Vision (3DV).

[6]  Iasonas Kokkinos,et al.  HoloPose: Holistic 3D Human Reconstruction In-The-Wild , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[7]  Ron Kimmel,et al.  Unsupervised Learning of Dense Shape Correspondence , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[8]  Young Min Kim,et al.  RL-GAN-Net: A Reinforcement Learning Agent Controlled GAN Network for Real-Time Point Cloud Shape Completion , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[9]  Leonidas J. Guibas,et al.  Deep Hough Voting for 3D Object Detection in Point Clouds , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

[10]  Silvio Savarese,et al.  4D Spatio-Temporal ConvNets: Minkowski Convolutional Neural Networks , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[11]  Matthias Zwicker,et al.  Render4Completion: Synthesizing Multi-View Depth Maps for 3D Shape Completion , 2019, 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW).

[12]  Nikolaus F. Troje,et al.  AMASS: Archive of Motion Capture As Surface Shapes , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

[13]  Leonidas J. Guibas,et al.  FrameNet: Learning Local Canonical Frames of 3D Surfaces From a Single RGB Image , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

[14]  Richard A. Newcombe,et al.  DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[15]  Ron Kimmel,et al.  Momen^et: Flavor the Moments in Learning to Classify Shapes , 2018, 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW).

[16]  Maks Ovsjanikov,et al.  Isospectralization, or How to Hear Shape, Style, and Correspondence , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[17]  Yue Wang,et al.  Dynamic Graph CNN for Learning on Point Clouds , 2018, ACM Trans. Graph..

[18]  Daniel Cohen-Or,et al.  MeshCNN: a network with an edge , 2019, ACM Trans. Graph..

[19]  Jiajun Wu,et al.  Learning Shape Priors for Single-View 3D Completion and Reconstruction , 2018, ECCV.

[20]  Anath Fischer,et al.  3DmFV: Three-Dimensional Point Cloud Classification in Real-Time Using Convolutional Neural Networks , 2018, IEEE Robotics and Automation Letters.

[21]  Mathieu Aubry,et al.  3D-CODED: 3D Correspondences by Deep Deformation , 2018, ECCV.

[22]  Cristian Sminchisescu,et al.  Monocular 3D Pose and Shape Estimation of Multiple People in Natural Scenes: The Importance of Multiple Scene Constraints , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[23]  Andreas Geiger,et al.  Learning 3D Shape Completion from Laser Scan Data with Weak Supervision , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[24]  Cordelia Schmid,et al.  BodyNet: Volumetric Inference of 3D Human Body Shapes , 2018, ECCV.

[25]  Mathieu Aubry,et al.  AtlasNet: A Papier-M\^ach\'e Approach to Learning 3D Surface Generation , 2018, CVPR 2018.

[26]  Mathieu Aubry,et al.  A Papier-Mache Approach to Learning 3D Surface Generation , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[27]  Alexander M. Bronstein,et al.  Deformable Shape Completion with Graph Convolutional Autoencoders , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[28]  Danfei Xu,et al.  PointFusion: Deep Sensor Fusion for 3D Bounding Box Estimation , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[29]  Laurens van der Maaten,et al.  3D Semantic Segmentation with Submanifold Sparse Convolutional Networks , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[30]  Bernhard Egger,et al.  Morphable Face Models - An Open Framework , 2017, 2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018).

[31]  Anath Fischer,et al.  3D Point Cloud Classification and Segmentation using 3D Modified Fisher Vector Representation for Convolutional Neural Networks , 2017, ArXiv.

[32]  Dimitrios Tzionas,et al.  Embodied hands , 2017, ACM Trans. Graph..

[33]  Luca Antiga,et al.  Automatic differentiation in PyTorch , 2017 .

[34]  Didier Stricker,et al.  Learning Quadrangulated Patches for 3D Shape Parameterization and Completion , 2017, 2017 International Conference on 3D Vision (3DV).

[35]  Michael J. Black,et al.  Dynamic FAUST: Registering Human Bodies in Motion , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[36]  Daniel Cremers,et al.  KillingFusion: Non-rigid 3D Reconstruction without Correspondences , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[37]  Edmond Boyer,et al.  Dynamic Filters in Graph Convolutional Networks , 2017, ArXiv.

[38]  Leonidas J. Guibas,et al.  PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space , 2017, NIPS.

[39]  Alexander M. Bronstein,et al.  Fully Spectral Partial Shape Matching , 2017, Comput. Graph. Forum.

[40]  Alexander M. Bronstein,et al.  Deep Functional Maps: Structured Prediction for Dense Shape Correspondence , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).

[41]  Ron Kimmel,et al.  Unrestricted Facial Geometry Reconstruction Using Image-to-Image Translation , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).

[42]  Cordelia Schmid,et al.  Learning from Synthetic Humans , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[43]  Leonidas J. Guibas,et al.  PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[44]  Matthias Nießner,et al.  Shape Completion Using 3D-Encoder-Predictor CNNs and Shape Synthesis , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[45]  Jonathan Masci,et al.  Geometric Deep Learning on Graphs and Manifolds Using Mixture Model CNNs , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[46]  Pierre Vandergheynst,et al.  Geometric Deep Learning: Going beyond Euclidean data , 2016, IEEE Signal Process. Mag..

[47]  Matan Sela,et al.  Learning Detailed Face Reconstruction from a Single Image , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[48]  Ron Kimmel,et al.  Fast Blended Transformations for Partial Shape Registration , 2016, Journal of Mathematical Imaging and Vision.

[49]  Daniel Cremers,et al.  Partial Functional Correspondence , 2017 .

[50]  Alexander M. Bronstein,et al.  Cloud Dictionary: Sparse Coding and Modeling for Point Clouds , 2016, ArXiv.

[51]  Matan Sela,et al.  3D Face Reconstruction by Learning from Synthetic Data , 2016, 2016 Fourth International Conference on 3D Vision (3DV).

[52]  Jonathan Masci,et al.  Learning shape correspondence with anisotropic convolutional neural networks , 2016, NIPS.

[53]  Qi-Xing Huang,et al.  Dense Human Body Correspondences Using Convolutional Networks , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[54]  Vladlen Koltun,et al.  Robust Nonrigid Registration by Convex Optimization , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

[55]  Eyal Ofek,et al.  Peeking Template Matching for Depth Extension , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

[56]  Michael J. Black,et al.  SMPL: A Skinned Multi-Person Linear Model , 2023 .

[57]  Dieter Fox,et al.  DynamicFusion: Reconstruction and tracking of non-rigid scenes in real-time , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[58]  Subhransu Maji,et al.  Multi-view Convolutional Neural Networks for 3D Shape Recognition , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

[59]  Pierre Vandergheynst,et al.  Geodesic Convolutional Neural Networks on Riemannian Manifolds , 2015, 2015 IEEE International Conference on Computer Vision Workshop (ICCVW).

[60]  Jianxiong Xiao,et al.  3D ShapeNets: A deep representation for volumetric shapes , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[61]  Michael J. Black,et al.  FAUST: Dataset and Evaluation for 3D Mesh Registration , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

[62]  Daniel Cremers,et al.  Dense Non-rigid Shape Correspondence Using Random Forests , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

[63]  Michael M. Kazhdan,et al.  Screened poisson surface reconstruction , 2013, TOGS.

[64]  Vladimir G. Kim,et al.  Blended intrinsic maps , 2011, ACM Trans. Graph..

[65]  Federico Tombari,et al.  Unique Signatures of Histograms for Local Surface Description , 2010, ECCV.

[66]  Alexander M. Bronstein,et al.  On reconstruction of non-rigid shapes with intrinsic regularization , 2009, 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops.

[67]  Alexander M. Bronstein,et al.  Expression-Invariant Representations of Faces , 2007, IEEE Transactions on Image Processing.

[68]  Aaron Hertzmann,et al.  Eurographics/ Acm Siggraph Symposium on Computer Animation (2006) Learning a Correlated Model of Identity and Pose-dependent Body Shape Variation for Real-time Synthesis , 2022 .

[69]  Alexander M. Bronstein,et al.  Facetoface: An Isometric Model for Facial Animation , 2006, AMDO.

[70]  Alfred M. Bruckstein,et al.  Matching Two-Dimensional Articulated Shapes Using Generalized Multidimensional Scaling , 2006, AMDO.

[71]  Alexander M. Bronstein,et al.  Robust Expression-Invariant Face Recognition from Partially Missing Data , 2006, ECCV.

[72]  Ron Kimmel,et al.  Generalized multidimensional scaling: A framework for isometry-invariant partial surface matching , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[73]  Alexander M. Bronstein,et al.  Three-Dimensional Face Recognition , 2005, International Journal of Computer Vision.

[74]  Dragomir Anguelov,et al.  SCAPE: shape completion and animation of people , 2005, ACM Trans. Graph..

[75]  Ron Kimmel,et al.  On Bending Invariant Signatures for Surfaces , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[76]  Alexander M. Bronstein,et al.  Expression-Invariant 3D Face Recognition , 2003, AVBPA.

[77]  Ron Kimmel,et al.  Bending invariant representations for surfaces , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[78]  Thomas Vetter,et al.  A morphable model for the synthesis of 3D faces , 1999, SIGGRAPH.

[79]  HoppeHugues,et al.  Surface Reconstruction from Unorganized Points , 1992 .

[80]  Paul J. Besl,et al.  Method for registration of 3-D shapes , 1992, Other Conferences.