Disentangled Implicit Shape and Pose Learning for Scalable 6D Pose Estimation

[1]  V. Lepetit,et al.  Templates for 3D Object Pose Estimation Revisited: Generalization to New Objects and Robustness to Occlusions , 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[2]  Q. Dou,et al.  SGPA: Structure-Guided Prior Adaptation for Category-Level 6D Object Pose Estimation , 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV).

[3]  Yang Xiao,et al.  PoseContrast: Class-Agnostic Object Viewpoint Estimation in the Wild with Pose-Aware Contrastive Learning , 2021, 2021 International Conference on 3D Vision (3DV).

[4]  Ales Leonardis,et al.  FS-Net: Fast Shape-based Network for Category-Level 6D Object Pose Estimation with Decoupled Rotation Mechanism , 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[5]  Kui Jia,et al.  DualPoseNet: Category-level 6D Object Pose and Size Estimation Using Dual Pose Network with Refined Learning of Pose Consistency , 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV).

[6]  Diane Bouchacourt,et al.  Addressing the Topological Defects of Disentanglement via Distributed Operators , 2021, ArXiv.

[7]  Giorgia Pitteri,et al.  3D Object Detection and Pose Estimation of Unseen Objects in Color Images with Local Surface Embeddings , 2020, ACCV.

[8]  Eric Brachmann,et al.  BOP Challenge 2020 on 6D Object Localization , 2020, ECCV Workshops.

[9]  Mathieu Aubry,et al.  CosyPose: Consistent multi-view multi-object 6D pose estimation , 2020, ECCV.

[10]  Jie Song,et al.  Category Level Object Pose Estimation via Neural Analysis-by-Synthesis , 2020, ECCV.

[11]  Gim Hee Lee,et al.  Shape Prior Deformation for Categorical 6D Object Pose and Size Estimation , 2020, ECCV.

[12]  John Martyn,et al.  Entanglement and Tensor Networks for Supervised Image Classification , 2020, ArXiv.

[13]  Wenping Wang,et al.  Edge Enhanced Implicit Orientation Learning With Geometric Prior for 6D Pose Estimation , 2020, IEEE Robotics and Automation Letters.

[14]  Vincent Lepetit,et al.  Recent Advances in 3D Object and Hand Pose Estimation , 2020, ArXiv.

[15]  Jiri Matas,et al.  EPOS: Estimating 6D Pose of Objects With Symmetries , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[16]  Hao Chen,et al.  Conditional Convolutions for Instance Segmentation , 2020, ECCV.

[17]  Geoffrey E. Hinton,et al.  A Simple Framework for Contrastive Learning of Visual Representations , 2020, ICML.

[18]  Kai Xu,et al.  Learning Canonical Shape Space for Category-Level 6D Object Pose and Size Estimation , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[19]  Tero Karras,et al.  Analyzing and Improving the Image Quality of StyleGAN , 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[20]  Dieter Fox,et al.  LatentFusion: End-to-End Differentiable Reconstruction and Rendering for Unseen Object Pose Estimation , 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[21]  Ross B. Girshick,et al.  Momentum Contrast for Unsupervised Visual Representation Learning , 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[22]  Zoltan-Csaba Marton,et al.  Augmented Autoencoders: Implicit 3D Orientation Learning for 6D Object Detection , 2019, International Journal of Computer Vision.

[23]  Xiangyang Ji,et al.  CDPN: Coordinates-Based Disentangled Pose Network for Real-Time RGB-Based 6-DoF Object Pose Estimation , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

[24]  Timothy Patten,et al.  Pix2Pose: Pixel-Wise Coordinate Regression of Objects for 6D Pose Estimation , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

[25]  Peter M. Roth,et al.  Location Field Descriptors: Single Image 3D Model Retrieval in the Wild , 2019, 2019 International Conference on 3D Vision (3DV).

[26]  Zoltan-Csaba Marton,et al.  Multi-Path Learning for Object Pose Estimation Across Domains , 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[27]  Szymon Rusinkiewicz,et al.  A symmetric objective function for ICP , 2019, ACM Trans. Graph..

[28]  Aapo Hyvärinen,et al.  Variational Autoencoders and Nonlinear ICA: A Unifying Framework , 2019, AISTATS.

[29]  Stefan Bauer,et al.  On the Fairness of Disentangled Representations , 2019, NeurIPS.

[30]  Haoruo Zhang,et al.  Detect in RGB, Optimize in Edge: Accurate 6D Pose Estimation for Texture-less Industrial Parts , 2019, 2019 International Conference on Robotics and Automation (ICRA).

[31]  Leonidas J. Guibas,et al.  Normalized Object Coordinate Space for Category-Level 6D Object Pose and Size Estimation , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[32]  Hujun Bao,et al.  PVNet: Pixel-Wise Voting Network for 6DoF Pose Estimation , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[33]  Timo Aila,et al.  A Style-Based Generator Architecture for Generative Adversarial Networks , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[34]  David Pfau,et al.  Towards a Definition of Disentangled Representations , 2018, ArXiv.

[35]  Bernhard Schölkopf,et al.  Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations , 2018, ICML.

[36]  Matthew Johnson-Roberson,et al.  SilhoNet: An RGB Method for 3D Object Pose Estimation and Grasp Planning. , 2018 .

[37]  Zoltan-Csaba Marton,et al.  Implicit 3D Orientation Learning for 6D Object Detection from RGB Images , 2018, ECCV.

[38]  Eric Brachmann,et al.  BOP: Benchmark for 6D Object Pose Estimation , 2018, ECCV.

[39]  Tom M. Mitchell,et al.  Contextual Parameter Generation for Universal Neural Machine Translation , 2018, EMNLP.

[40]  Oriol Vinyals,et al.  Representation Learning with Contrastive Predictive Coding , 2018, ArXiv.

[41]  Yoshua Bengio,et al.  Feature-wise transformations , 2018, Distill.

[42]  Stella X. Yu,et al.  Unsupervised Feature Learning via Non-parametric Instance Discrimination , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[43]  Qi-Xing Huang,et al.  StarMap for Category-Agnostic Keypoint and Viewpoint Estimation , 2018, ECCV.

[44]  Pascal Fua,et al.  Real-Time Seamless Single Shot 6D Object Pose Prediction , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[45]  Dieter Fox,et al.  PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes , 2017, Robotics: Science and Systems.

[46]  Nassir Navab,et al.  SSD-6D: Making RGB-Based 3D Detection and 6D Pose Estimation Great Again , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).

[47]  Kaiming He,et al.  Focal Loss for Dense Object Detection , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).

[48]  Ross B. Girshick,et al.  Focal Loss for Dense Object Detection , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[49]  Lukasz Kaiser,et al.  Attention is All you Need , 2017, NIPS.

[50]  Vincent Lepetit,et al.  BB8: A Scalable, Accurate, Robust to Partial Occlusion Method for Predicting the 3D Poses of Challenging Objects without Using Depth , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).

[51]  Ross B. Girshick,et al.  Mask R-CNN , 2017, 1703.06870.

[52]  Serge J. Belongie,et al.  Arbitrary Style Transfer in Real-Time with Adaptive Instance Normalization , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).

[53]  Manolis I. A. Lourakis,et al.  T-LESS: An RGB-D Dataset for 6D Pose Estimation of Texture-Less Objects , 2017, 2017 IEEE Winter Conference on Applications of Computer Vision (WACV).

[54]  Christopher Burgess,et al.  beta-VAE: Learning Basic Visual Concepts with a Constrained Variational Framework , 2016, ICLR 2016.

[55]  J. Schulman,et al.  InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets , 2016, NIPS.

[56]  Eric Brachmann,et al.  Uncertainty-Driven 6D Pose Estimation of Objects and Scenes from a Single RGB Image , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[57]  Leonidas J. Guibas,et al.  ShapeNet: An Information-Rich 3D Model Repository , 2015, ArXiv.

[58]  Moo K. Chung,et al.  4D hyperspherical harmonic (HyperSPHARM) representation of surface anatomy: A holistic treatment of multiple disconnected anatomical structures , 2015, Medical Image Anal..

[59]  Jimmy Ba,et al.  Adam: A Method for Stochastic Optimization , 2014, ICLR.

[60]  Vincent Lepetit,et al.  Model Based Training, Detection and Pose Estimation of Texture-Less 3D Objects in Heavily Cluttered Scenes , 2012, ACCV.

[61]  Pascal Vincent,et al.  Representation Learning: A Review and New Perspectives , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[62]  Álvaro González.  Measurement of Areas on a Sphere Using Fibonacci and Latitude–Longitude Lattices , 2009, 0912.4540.

[63]  Joshua B. Tenenbaum,et al.  Separating Style and Content with Bilinear Models , 2000, Neural Computation.

[64]  Lin Zhao.  Spherical and Spheroidal Harmonics: Examples and Computations , 2017 .

[65]  Vincent Lepetit,et al.  Simultaneous Recognition and Homography Extraction of Local Patches with a Simple Linear Classifier , 2008, BMVC.