{"list":"other","total":58,"rows":[{"id":"1912.01703","title":"PyTorch: An Imperative Style, High-Performance Deep Learning Library","created":"2019-12-03","cited_by_count":20305},{"id":"1812.07035","title":"On the Continuity of Rotation Representations in Neural Networks","created":"2018-12-17","cited_by_count":1214},{"id":"1602.07576","title":"Group Equivariant Convolutional Networks","created":"2016-02-24","cited_by_count":1165},{"id":"1711.00199","title":"PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes","created":"2017-11-01","cited_by_count":775},{"id":"1901.02970","title":"Normalized Object Coordinate Space for Category-Level 6D Object Pose and Size Estimation","created":"2019-01-09","cited_by_count":495},{"id":"1801.10130","title":"Spherical CNNs","created":"2018-01-30","cited_by_count":456},{"id":"1911.08251","title":"General $E(2)$-Equivariant Steerable CNNs","created":"2019-11-19","cited_by_count":446},{"id":"1711.06721","title":"Learning SO(3) Equivariant Representations with Spherical CNNs","created":"2017-11-17","cited_by_count":248},{"id":"1704.00390","title":"Geometric Loss Functions for Camera Pose Regression with Deep Learning","created":"2017-04-02","cited_by_count":224},{"id":"1612.02401","title":"DeMoN: Depth and Motion Network for Learning Monocular Stereo","created":"2016-12-07","cited_by_count":201},{"id":"1806.09231","title":"Clebsch-Gordan Nets: a Fully Fourier Space Spherical Convolutional Neural Network","created":"2018-06-24","cited_by_count":171},{"id":"2210.10716","title":"CroCo: Self-Supervised Pre-training for 3D Vision Tasks by Cross-View Completion","created":"2022-10-19","cited_by_count":160},{"id":"2306.15667","title":"PoseDiffusion: Solving Pose Estimation via Diffusion-aided Bundle Adjustment","created":"2023-06-27","cited_by_count":147},{"id":"2402.14817","title":"Cameras as Rays: Pose Estimation via Ray Diffusion","created":"2024-02-22","cited_by_count":131},{"id":"2208.05963","title":"RelPose: Predicting Probabilistic Relative Rotation for Single Objects in the Wild","created":"2022-08-11","cited_by_count":102},{"id":"2210.10770","title":"LaMAR: Benchmarking Localization and Mapping for Augmented Reality","created":"2022-10-19","cited_by_count":100},{"id":"1906.03631","title":"Overcoming Limitations of Mixture Density Networks: A Sampling and Fitting Framework for Multimodal Future Prediction","created":"2019-06-09","cited_by_count":96},{"id":"2101.01132","title":"Volumetric Grasping Network: Real-time 6 DOF Grasp Detection in Clutter","created":"2021-01-04","cited_by_count":95},{"id":"1505.05641","title":"Render for CNN: Viewpoint Estimation in Images Using CNNs Trained with Rendered 3D Model Views","created":"2015-05-21","cited_by_count":94},{"id":"2305.04926","title":"RelPose++: Recovering 6D Poses from Sparse-view Observations","created":"2023-05-08","cited_by_count":87},{"id":"2006.14616","title":"An Analysis of SVD for Deep Rotation Estimation","created":"2020-06-25","cited_by_count":86},{"id":"2103.16317","title":"Deep Regression on Manifolds: A 3D Rotation Case Study","created":"2021-03-30","cited_by_count":67},{"id":"1809.07417","title":"Deep Part Induction from Articulated Object Pairs","created":"2018-09-19","cited_by_count":66},{"id":"2012.15000","title":"DeepSphere: a graph-based spherical CNN","created":"2020-12-30","cited_by_count":66},{"id":"2106.05965","title":"Implicit-PDF: Non-Parametric Representation of Probability Distributions on the Rotation Manifold","created":"2021-06-10","cited_by_count":65},{"id":"1411.6067","title":"Viewpoints and Keypoints","created":"2014-11-22","cited_by_count":59},{"id":"1909.05215","title":"Reconstructing continuous distributions of 3D protein structure from cryo-EM images","created":"2019-09-11","cited_by_count":56},{"id":"2006.10731","title":"Spin-Weighted Spherical CNNs","created":"2020-06-18","cited_by_count":50},{"id":"2106.03336","title":"Wide-Baseline Relative Camera Pose Estimation with Directional Learning","created":"2021-06-07","cited_by_count":49},{"id":"2101.06605","title":"MultiBodySync: Multi-Body Segmentation and Motion Estimation via 3D Scan Synchronization","created":"2021-01-17","cited_by_count":46},{"id":"1805.03430","title":"Deep Directional Statistics: Pose Estimation with Uncertainty Quantification","created":"2018-05-09","cited_by_count":45},{"id":"2012.11002","title":"Deep Bingham Networks: Dealing with Uncertainty and Ambiguity in Pose Estimation","created":"2020-12-20","cited_by_count":43},{"id":"2104.13530","title":"Extreme Rotation Estimation using Dense Correlation Volumes","created":"2021-04-28","cited_by_count":42},{"id":"2404.11735","title":"Learning with 3D rotations, a hitchhiker's guide to SO(3)","created":"2024-04-17","cited_by_count":42},{"id":"1912.12098","title":"Quaternion Equivariant Capsule Networks for 3D Point Clouds","created":"2019-12-27","cited_by_count":41},{"id":"1904.05404","title":"Spherical Regression: Learning Viewpoints, Surface Normals and 3D Rotations on n-Spheres","created":"2019-04-10","cited_by_count":37},{"id":"2006.09740","title":"Probabilistic orientation estimation with matrix Fisher distributions","created":"2020-06-17","cited_by_count":36},{"id":"2110.11657","title":"Projective Manifold Gradient Layer for Deep Rotation Regression","created":"2021-10-22","cited_by_count":31},{"id":"2010.11661","title":"Efficient Generalized Spherical CNNs","created":"2020-10-09","cited_by_count":29},{"id":"1802.10367","title":"Deep-6DPose: Recovering 6D Object Pose from a Single RGB Image","created":"2018-02-28","cited_by_count":26},{"id":"2204.08613","title":"Self-Supervised Equivariant Learning for Oriented Keypoint Detection","created":"2022-04-19","cited_by_count":26},{"id":"2004.04807","title":"6D Camera Relocalization in Ambiguous Scenes via Continuous Multimodal Inference","created":"2020-04-09","cited_by_count":23},{"id":"2303.15472","title":"Learning Rotation-Equivariant Features for Visual Correspondence","created":"2023-03-25","cited_by_count":23},{"id":"2306.05420","title":"Scaling Spherical CNNs","created":"2023-06-08","cited_by_count":21},{"id":"2206.08362","title":"Unified Fourier-based Kernel and Nonlinearity Design for Equivariant Networks on Homogeneous Spaces","created":"2022-06-16","cited_by_count":20},{"id":"1805.03225","title":"A Mixed Classification-Regression Framework for 3D Pose Estimation from 2D Images","created":"2018-05-08","cited_by_count":19},{"id":"2302.13926","title":"Image to Sphere: Learning Equivariant Features for Efficient Pose Prediction","created":"2023-02-27","cited_by_count":18},{"id":"2203.15765","title":"FisherMatch: Semi-Supervised Rotation Regression via Entropy-based Filtering","created":"2022-03-29","cited_by_count":16},{"id":"2304.03937","title":"Delving into Discrete Normalizing Flows on SO(3) Manifold for Probabilistic Rotation Modeling","created":"2023-04-08","cited_by_count":14},{"id":"1808.05498","title":"Occlusion Resistant Object Rotation Regression from Point Cloud Segments","created":"2018-08-16","cited_by_count":9},{"id":"2206.07259","title":"Self-Supervised Learning of Image Scale and Orientation","created":"2022-06-15","cited_by_count":9},{"id":"2303.01743","title":"A Laplace-inspired Distribution on SO(3) for Probabilistic Rotation Estimation","created":"2023-03-03","cited_by_count":9},{"id":"2307.03704","title":"Equivariant Single View Pose Prediction Via Induced and Restricted Representations","created":"2023-07-07","cited_by_count":6},{"id":"2311.14670","title":"Differentiable and accelerated spherical harmonic and Wigner transforms","created":"2023-11-24","cited_by_count":6},{"id":"2401.05396","title":"Loss it right: Euclidean and Riemannian Metrics in Learning-based Visual Odometry","created":"2023-12-19","cited_by_count":6},{"id":"2104.01103","title":"Semi-supervised Viewpoint Estimation with Geometry-aware Conditional Generation","created":"2021-04-02","cited_by_count":5},{"id":"2207.08925","title":"Image to Icosahedral Projection for $\\mathrm{SO}(3)$ Object Reasoning from Single-View Images","created":"2022-07-18","cited_by_count":4},{"id":"2212.00435","title":"ViewNet: Unsupervised Viewpoint Estimation from Conditional Generation","created":"2022-12-01","cited_by_count":3}],"next_cursor":null}