{"list":"other","total":55,"rows":[{"id":"1512.03385","title":"Deep Residual Learning for Image Recognition","created":"2015-12-10","cited_by_count":52096},{"id":"2304.02643","title":"Segment Anything","created":"2023-04-05","cited_by_count":8234},{"id":"2005.12872","title":"End-to-End Object Detection with Transformers","created":"2020-05-26","cited_by_count":7414},{"id":"1612.03144","title":"Feature Pyramid Networks for Object Detection","created":"2016-12-09","cited_by_count":5036},{"id":"1306.0895","title":"Sinkhorn Distances: Lightspeed Computation of Optimal Transportation Distances","created":"2013-06-04","cited_by_count":2316},{"id":"2006.16236","title":"Transformers are RNNs: Fast Autoregressive Transformers with Linear Attention","created":"2020-06-29","cited_by_count":2022},{"id":"2305.05665","title":"ImageBind: One Embedding Space To Bind Them All","created":"2023-05-09","cited_by_count":1175},{"id":"2104.00680","title":"LoFTR: Detector-Free Local Feature Matching with Transformers","created":"2021-04-01","cited_by_count":984},{"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":"2204.11918","title":"Google Scanned Objects: A High-Quality Dataset of 3D Scanned Household Items","created":"2022-04-25","cited_by_count":612},{"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":"2002.10857","title":"Circle Loss: A Unified Perspective of Pair Similarity Optimization","created":"2020-02-25","cited_by_count":403},{"id":"1812.11788","title":"PVNet: Pixel-wise Voting Network for 6DoF Pose Estimation","created":"2018-12-31","cited_by_count":385},{"id":"1901.04780","title":"DenseFusion: 6D Object Pose Estimation by Iterative Dense Fusion","created":"2019-01-15","cited_by_count":355},{"id":"2011.13005","title":"PREDATOR: Registration of 3D Point Clouds with Low Overlap","created":"2020-11-25","cited_by_count":290},{"id":"2008.08465","title":"CosyPose: Consistent multi-view multi-object 6D pose estimation","created":"2020-08-19","cited_by_count":287},{"id":"1808.08319","title":"BOP: Benchmark for 6D Object Pose Estimation","created":"2018-08-24","cited_by_count":254},{"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":"1701.05498","title":"T-LESS: An RGB-D Dataset for 6D Pose Estimation of Texture-less Objects","created":"2017-01-19","cited_by_count":210},{"id":"1911.04231","title":"PVN3D: A Deep Point-wise 3D Keypoints Voting Network for 6DoF Pose Estimation","created":"2019-11-11","cited_by_count":204},{"id":"2202.06688","title":"Geometric Transformer for Fast and Robust Point Cloud Registration","created":"2022-02-14","cited_by_count":202},{"id":"2212.06870","title":"MegaPose: 6D Pose Estimation of Novel Objects via Render & Compare","created":"2022-12-13","cited_by_count":201},{"id":"1902.11020","title":"DPOD: 6D Pose Object Detector and Refiner","created":"2019-02-28","cited_by_count":189},{"id":"1711.10871","title":"PointFusion: Deep Sensor Fusion for 3D Bounding Box Estimation","created":"2017-11-29","cited_by_count":170},{"id":"2205.12257","title":"OnePose: One-Shot Object Pose Estimation without CAD Models","created":"2022-05-24","cited_by_count":157},{"id":"2110.14076","title":"CoFiNet: Reliable Coarse-to-fine Correspondences for Robust Point Cloud Registration","created":"2021-10-26","cited_by_count":152},{"id":"2102.12145","title":"GDRNPP: A Geometry-guided and Fully Learning-based Object Pose Estimator","created":"2021-02-24","cited_by_count":148},{"id":"2103.02242","title":"FFB6D: A Full Flow Bidirectional Fusion Network for 6D Pose Estimation","created":"2021-03-03","cited_by_count":144},{"id":"2204.10776","title":"Gen6D: Generalizable Model-Free 6-DoF Object Pose Estimation from RGB Images","created":"2022-04-22","cited_by_count":121},{"id":"2203.09418","title":"ZebraPose: Coarse to Fine Surface Encoding for 6DoF Object Pose Estimation","created":"2022-03-17","cited_by_count":116},{"id":"2301.07673","title":"OnePose++: Keypoint-Free One-Shot Object Pose Estimation without CAD Models","created":"2023-01-18","cited_by_count":115},{"id":"2111.13489","title":"SurfEmb: Dense and Continuous Correspondence Distributions for Object Pose Estimation with Learnt Surface Embeddings","created":"2021-11-26","cited_by_count":95},{"id":"2203.07918","title":"GPV-Pose: Category-level Object Pose Estimation via Geometry-guided Point-wise Voting","created":"2022-03-15","cited_by_count":94},{"id":"2307.11067","title":"CNOS: A Strong Baseline for CAD-based Novel Object Segmentation","created":"2023-07-20","cited_by_count":87},{"id":"2111.12591","title":"Lepard: Learning partial point cloud matching in rigid and deformable scenes","created":"2021-11-24","cited_by_count":85},{"id":"2203.15533","title":"OSOP: A Multi-Stage One Shot Object Pose Estimation Framework","created":"2022-03-29","cited_by_count":81},{"id":"1512.07506","title":"Recovering 6D Object Pose and Predicting Next-Best-View in the Crowd","created":"2015-12-23","cited_by_count":79},{"id":"1609.09475","title":"Multi-view Self-supervised Deep Learning for 6D Pose Estimation in the Amazon Picking Challenge","created":"2016-09-29","cited_by_count":70},{"id":"2302.13075","title":"BOP Challenge 2022 on Detection, Segmentation and Pose Estimation of Specific Rigid Objects","created":"2023-02-25","cited_by_count":70},{"id":"2303.08231","title":"Rotation-Invariant Transformer for Point Cloud Matching","created":"2023-03-14","cited_by_count":69},{"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":"2109.00182","title":"You Only Hypothesize Once: Point Cloud Registration with Rotation-equivariant Descriptors","created":"2021-09-01","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":"1502.05908","title":"Learning Descriptors for Object Recognition and 3D Pose Estimation","created":"2015-02-20","cited_by_count":60},{"id":"2203.04802","title":"NeRF-Pose: A First-Reconstruct-Then-Regress Approach for Weakly-supervised 6D Object Pose Estimation","created":"2022-03-09","cited_by_count":58},{"id":"1908.00151","title":"Multi-path Learning for Object Pose Estimation Across Domains","created":"2019-08-01","cited_by_count":52},{"id":"2203.01072","title":"OVE6D: Object Viewpoint Encoding for Depth-based 6D Object Pose Estimation","created":"2022-03-02","cited_by_count":43},{"id":"1807.02062","title":"Stereo Vision-based Semantic 3D Object and Ego-motion Tracking for Autonomous Driving","created":"2018-07-05","cited_by_count":26},{"id":"2104.13526","title":"ZePHyR: Zero-shot Pose Hypothesis Rating","created":"2021-04-28","cited_by_count":26},{"id":"2209.13252","title":"RIGA: Rotation-Invariant and Globally-Aware Descriptors for Point Cloud Registration","created":"2022-09-27","cited_by_count":25},{"id":"2009.12678","title":"I Like to Move It: 6D Pose Estimation as an Action Decision Process","created":"2020-09-26","cited_by_count":22},{"id":"2308.05438","title":"Deep Fusion Transformer Network with Weighted Vector-Wise Keypoints Voting for Robust 6D Object Pose Estimation","created":"2023-08-10","cited_by_count":16},{"id":"2303.05308","title":"SpyroPose: SE(3) Pyramids for Object Pose Distribution Estimation","created":"2023-03-09","cited_by_count":14},{"id":"2011.05669","title":"A Hybrid Approach for 6DoF Pose Estimation","created":"2020-11-11","cited_by_count":13},{"id":"2209.09659","title":"Ki-Pode: Keypoint-based Implicit Pose Distribution Estimation of Rigid Objects","created":"2022-09-20","cited_by_count":7}],"next_cursor":null}