{"list":"other","total":64,"rows":[{"id":"1512.03385","title":"Deep Residual Learning for Image Recognition","created":"2015-12-10","cited_by_count":52096},{"id":"2006.10739","title":"Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains","created":"2020-06-18","cited_by_count":2200},{"id":"1911.11763","title":"SuperGlue: Learning Feature Matching with Graph Neural Networks","created":"2019-11-26","cited_by_count":1443},{"id":"1712.07629","title":"SuperPoint: Self-Supervised Interest Point Detection and Description","created":"2017-12-20","cited_by_count":1320},{"id":"1812.07035","title":"On the Continuity of Rotation Representations in Neural Networks","created":"2018-12-17","cited_by_count":1214},{"id":"1502.00956","title":"ORB-SLAM: a Versatile and Accurate Monocular SLAM System","created":"2015-02-03","cited_by_count":988},{"id":"2007.11898","title":"ORB-SLAM3: An Accurate Open-Source Library for Visual, Visual-Inertial and Multi-Map SLAM","created":"2020-07-23","cited_by_count":878},{"id":"1610.06475","title":"ORB-SLAM2: an Open-Source SLAM System for Monocular, Stereo and RGB-D Cameras","created":"2016-10-20","cited_by_count":806},{"id":"1704.07813","title":"Unsupervised Learning of Depth and Ego-Motion from Video","created":"2017-04-25","cited_by_count":782},{"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":"2108.10869","title":"DROID-SLAM: Deep Visual SLAM for Monocular, Stereo, and RGB-D Cameras","created":"2021-08-24","cited_by_count":687},{"id":"2109.00512","title":"Common Objects in 3D: Large-Scale Learning and Evaluation of Real-life 3D Category Reconstruction","created":"2021-09-01","cited_by_count":652},{"id":"2104.06405","title":"BARF: Bundle-Adjusting Neural Radiance Fields","created":"2021-04-13","cited_by_count":642},{"id":"1812.03506","title":"From Coarse to Fine: Robust Hierarchical Localization at Large Scale","created":"2018-12-09","cited_by_count":559},{"id":"1607.02565","title":"Direct Sparse Odometry","created":"2016-07-09","cited_by_count":485},{"id":"1904.11486","title":"Making Convolutional Networks Shift-Invariant Again","created":"2019-04-25","cited_by_count":391},{"id":"1901.04780","title":"DenseFusion: 6D Object Pose Estimation by Iterative Dense Fusion","created":"2019-01-15","cited_by_count":355},{"id":"1803.02276","title":"GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera Pose","created":"2018-03-06","cited_by_count":342},{"id":"1603.09114","title":"LIFT: Learned Invariant Feature Transform","created":"2016-03-30","cited_by_count":306},{"id":"1711.10006","title":"SSD-6D: Making RGB-based 3D detection and 6D pose estimation great again","created":"2017-11-27","cited_by_count":243},{"id":"1804.04610","title":"Pix3D: Dataset and Methods for Single-Image 3D Shape Modeling","created":"2018-04-12","cited_by_count":218},{"id":"1711.08848","title":"Real-Time Seamless Single Shot 6D Object Pose Prediction","created":"2017-11-24","cited_by_count":210},{"id":"1612.02401","title":"DeMoN: Depth and Motion Network for Learning Monocular Stereo","created":"2016-12-07","cited_by_count":201},{"id":"2108.08291","title":"Pixel-Perfect Structure-from-Motion with Featuremetric Refinement","created":"2021-08-18","cited_by_count":200},{"id":"1910.02490","title":"Kimera: an Open-Source Library for Real-Time Metric-Semantic Localization and Mapping","created":"2019-10-06","cited_by_count":184},{"id":"1802.05522","title":"Unsupervised Learning of Depth and Ego-Motion from Monocular Video Using 3D Geometric Constraints","created":"2018-02-15","cited_by_count":179},{"id":"1709.08429","title":"DeepVO: Towards End-to-End Visual Odometry with Deep Recurrent Convolutional Neural Networks","created":"2017-09-25","cited_by_count":175},{"id":"1806.04807","title":"BA-Net: Dense Bundle Adjustment Network","created":"2018-06-13","cited_by_count":175},{"id":"1902.01275","title":"Implicit 3D Orientation Learning for 6D Object Detection from RGB Images","created":"2019-02-04","cited_by_count":170},{"id":"2007.15649","title":"Perceiving 3D Human-Object Spatial Arrangements from a Single Image in the Wild","created":"2020-07-30","cited_by_count":152},{"id":"1912.05524","title":"GLU-Net: Global-Local Universal Network for Dense Flow and Correspondences","created":"2019-12-11","cited_by_count":139},{"id":"2110.07604","title":"NeRS: Neural Reflectance Surfaces for Sparse-view 3D Reconstruction in the Wild","created":"2021-10-14","cited_by_count":136},{"id":"1509.05909","title":"Modelling Uncertainty in Deep Learning for Camera Relocalization","created":"2015-09-19","cited_by_count":134},{"id":"2011.00359","title":"TartanVO: A Generalizable Learning-based VO","created":"2020-10-31","cited_by_count":108},{"id":"2001.01869","title":"HybridPose: 6D Object Pose Estimation under Hybrid Representations","created":"2020-01-07","cited_by_count":107},{"id":"2004.13324","title":"Learning Feature Descriptors using Camera Pose Supervision","created":"2020-04-28","cited_by_count":104},{"id":"1909.10159","title":"Self-supervised 6D Object Pose Estimation for Robot Manipulation","created":"2019-09-23","cited_by_count":101},{"id":"1905.09304","title":"PoseRBPF: A Rao-Blackwellized Particle Filter for 6D Object Pose Tracking","created":"2019-05-22","cited_by_count":91},{"id":"1704.07804","title":"SfM-Net: Learning of Structure and Motion from Video","created":"2017-04-25","cited_by_count":89},{"id":"1808.01900","title":"DeepTAM: Deep Tracking and Mapping","created":"2018-08-06","cited_by_count":87},{"id":"2111.09996","title":"LOLNeRF: Learn from One Look","created":"2021-11-19","cited_by_count":84},{"id":"1606.03558","title":"Universal Correspondence Network","created":"2016-06-11","cited_by_count":82},{"id":"1804.03959","title":"Making Deep Heatmaps Robust to Partial Occlusions for 3D Object Pose Estimation","created":"2018-04-11","cited_by_count":74},{"id":"1912.09697","title":"DeepSFM: Structure From Motion Via Deep Bundle Adjustment","created":"2019-12-20","cited_by_count":70},{"id":"1812.00287","title":"Explaining the Ambiguity of Object Detection and 6D Pose From Visual Data","created":"2018-12-01","cited_by_count":68},{"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":"2104.00633","title":"RePOSE: Fast 6D Object Pose Refinement via Deep Texture Rendering","created":"2021-04-01","cited_by_count":63},{"id":"1909.02533","title":"C3DPO: Canonical 3D Pose Networks for Non-Rigid Structure From Motion","created":"2019-09-05","cited_by_count":61},{"id":"2106.03336","title":"Wide-Baseline Relative Camera Pose Estimation with Directional Learning","created":"2021-06-07","cited_by_count":49},{"id":"1702.01381","title":"Relative Camera Pose Estimation Using Convolutional Neural Networks","created":"2017-02-05","cited_by_count":47},{"id":"2011.04307","title":"EfficientPose: An efficient, accurate and scalable end-to-end 6D multi object pose estimation approach","created":"2020-11-09","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":"2007.08988","title":"Online Invariance Selection for Local Feature Descriptors","created":"2020-07-17","cited_by_count":41},{"id":"1906.05105","title":"Pose from Shape: Deep Pose Estimation for Arbitrary 3D Objects","created":"2019-06-12","cited_by_count":39},{"id":"2006.09740","title":"Probabilistic orientation estimation with matrix Fisher distributions","created":"2020-06-17","cited_by_count":36},{"id":"2012.04718","title":"Canonical Capsules: Self-Supervised Capsules in Canonical Pose","created":"2020-12-08","cited_by_count":30},{"id":"1703.01661","title":"SegICP: Integrated Deep Semantic Segmentation and Pose Estimation","created":"2017-03-05","cited_by_count":29},{"id":"1705.03951","title":"Learning 3D Object Categories by Looking Around Them","created":"2017-05-10","cited_by_count":26},{"id":"2110.05472","title":"Differentiable Stereopsis: Meshes from multiple views using differentiable rendering","created":"2021-10-11","cited_by_count":26},{"id":"1904.06577","title":"Direct Sparse Mapping","created":"2019-04-13","cited_by_count":25},{"id":"2003.08348","title":"Multi-View Optimization of Local Feature Geometry","created":"2020-03-18","cited_by_count":24},{"id":"2007.01418","title":"Learning Orientation Distributions for Object Pose Estimation","created":"2020-07-02","cited_by_count":18},{"id":"1810.05780","title":"Pose Estimation for Objects with Rotational Symmetry","created":"2018-10-13","cited_by_count":15},{"id":"2110.11636","title":"Occlusion-Robust Object Pose Estimation with Holistic Representation","created":"2021-10-22","cited_by_count":6}],"next_cursor":null}