暂无分享,去创建一个
Jonathan T. Barron | Yen-Chen Lin | Tsung-Yi Lin | Phillip Isola | Pete Florence | Alberto Rodriguez
[1] Vladimir G. Kim,et al. Photometric Mesh Optimization for Video-Aligned 3D Object Reconstruction , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[2] Siddhartha S. Srinivasa,et al. The MOPED framework: Object recognition and pose estimation for manipulation , 2011, Int. J. Robotics Res..
[3] Dieter Fox,et al. PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes , 2017, Robotics: Science and Systems.
[4] Andreas Geiger,et al. Differentiable Volumetric Rendering: Learning Implicit 3D Representations Without 3D Supervision , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[5] Wei Gao,et al. kPAM: KeyPoint Affordances for Category-Level Robotic Manipulation , 2019, ISRR.
[6] Silvio Savarese,et al. DenseFusion: 6D Object Pose Estimation by Iterative Dense Fusion , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[7] Andrea Palazzi,et al. End-to-End 6-DoF Object Pose Estimation Through Differentiable Rasterization , 2018, ECCV Workshops.
[8] Dieter Fox,et al. Deep Object Pose Estimation for Semantic Robotic Grasping of Household Objects , 2018, CoRL.
[9] Russ Tedrake,et al. Label Fusion: A Pipeline for Generating Ground Truth Labels for Real RGBD Data of Cluttered Scenes , 2017, 2018 IEEE International Conference on Robotics and Automation (ICRA).
[10] Raquel Urtasun,et al. Deep Feedback Inverse Problem Solver , 2021, ECCV.
[11] Tomasz Malisiewicz,et al. SuperGlue: Learning Feature Matching With Graph Neural Networks , 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[12] Xiaowei Zhou,et al. 6-DoF object pose from semantic keypoints , 2017, 2017 IEEE International Conference on Robotics and Automation (ICRA).
[13] Jaakko Lehtinen,et al. Learning to Predict 3D Objects with an Interpolation-based Differentiable Renderer , 2019, NeurIPS.
[14] Simon Lucey,et al. SDF-SRN: Learning Signed Distance 3D Object Reconstruction from Static Images , 2020, NeurIPS.
[15] Andrew W. Fitzgibbon,et al. Exploiting uncertainty in regression forests for accurate camera relocalization , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[16] Robert C. Bolles,et al. Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography , 1981, CACM.
[17] 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).
[18] Tat-Seng Chua,et al. Neural Sparse Voxel Fields , 2020, NeurIPS.
[19] 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).
[20] Jonathan T. Barron,et al. NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis , 2020, ECCV.
[21] Tomasz Malisiewicz,et al. SuperPoint: Self-Supervised Interest Point Detection and Description , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
[22] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[23] Luc Van Gool,et al. Simultaneous Object Recognition and Segmentation from Single or Multiple Model Views , 2006, International Journal of Computer Vision.
[24] Hans Wallach. Über visuell wahrgenommene Bewegungsrichtung , 1935 .
[25] Zoltan-Csaba Marton,et al. Implicit 3D Orientation Learning for 6D Object Detection from RGB Images , 2018, ECCV.
[26] Slobodan Ilic,et al. DPOD: 6D Pose Object Detector and Refiner , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[27] Sven Behnke,et al. RGB-D object recognition and pose estimation based on pre-trained convolutional neural network features , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).
[28] Jie Song,et al. Category Level Object Pose Estimation via Neural Analysis-by-Synthesis , 2020, ECCV.
[29] Pascal Fua,et al. Real-Time Seamless Single Shot 6D Object Pose Prediction , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[30] Federico Tombari,et al. Self6D: Self-Supervised Monocular 6D Object Pose Estimation , 2020, ECCV.
[31] Vincent Lepetit,et al. Model Based Training, Detection and Pose Estimation of Texture-Less 3D Objects in Heavily Cluttered Scenes , 2012, ACCV.
[32] Nassir Navab,et al. Explaining the Ambiguity of Object Detection and 6D Pose From Visual Data , 2018, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[33] Eric Brachmann,et al. BOP: Benchmark for 6D Object Pose Estimation , 2018, ECCV.
[34] James T. Kajiya,et al. Ray tracing volume densities , 1984, SIGGRAPH.
[35] Cordelia Schmid,et al. 3D Object Modeling and Recognition Using Local Affine-Invariant Image Descriptors and Multi-View Spatial Constraints , 2006, International Journal of Computer Vision.
[36] 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).
[37] Alexei A. Efros,et al. Seeing 3D Chairs: Exemplar Part-Based 2D-3D Alignment Using a Large Dataset of CAD Models , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[38] Yi Li,et al. DeepIM: Deep Iterative Matching for 6D Pose Estimation , 2018, International Journal of Computer Vision.
[39] Adrien Gaidon,et al. Differentiable Rendering: A Survey , 2020, ArXiv.
[40] Jonathan Tompson,et al. Discovery of Latent 3D Keypoints via End-to-end Geometric Reasoning , 2018, NeurIPS.
[41] Sebastian Nowozin,et al. Occupancy Networks: Learning 3D Reconstruction in Function Space , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[42] Dieter Fox,et al. Self-Supervised Visual Descriptor Learning for Dense Correspondence , 2017, IEEE Robotics and Automation Letters.
[43] Andrew W. Fitzgibbon,et al. Scene Coordinate Regression Forests for Camera Relocalization in RGB-D Images , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[44] 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).
[45] Jonathan T. Barron,et al. NeRF in the Wild: Neural Radiance Fields for Unconstrained Photo Collections , 2020, ArXiv.
[46] Nelson L. Max,et al. Optical Models for Direct Volume Rendering , 1995, IEEE Trans. Vis. Comput. Graph..
[47] Ravi Ramamoorthi,et al. Local Light Field Fusion: Practical View Synthesis with Prescriptive Sampling Guidelines , 2019 .
[48] Gordon Wetzstein,et al. Scene Representation Networks: Continuous 3D-Structure-Aware Neural Scene Representations , 2019, NeurIPS.