{"list":"other","total":52,"rows":[{"id":"1706.03762","title":"Attention Is All You Need","created":"2017-06-12","cited_by_count":60361},{"id":"1412.6980","title":"Adam: A Method for Stochastic Optimization","created":"2014-12-22","cited_by_count":37240},{"id":"2005.12872","title":"End-to-End Object Detection with Transformers","created":"2020-05-26","cited_by_count":7414},{"id":"1704.04861","title":"MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications","created":"2017-04-17","cited_by_count":3845},{"id":"2010.04159","title":"Deformable DETR: Deformable Transformers for End-to-End Object Detection","created":"2020-10-08","cited_by_count":3422},{"id":"1512.02325","title":"SSD: Single Shot MultiBox Detector","created":"2015-12-08","cited_by_count":3130},{"id":"2106.08254","title":"BEiT: BERT Pre-Training of Image Transformers","created":"2021-06-15","cited_by_count":2375},{"id":"2103.15691","title":"ViViT: A Video Vision Transformer","created":"2021-03-29","cited_by_count":1620},{"id":"2106.13230","title":"Video Swin Transformer","created":"2021-06-24","cited_by_count":1091},{"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":"1611.07759","title":"Multi-View 3D Object Detection Network for Autonomous Driving","created":"2016-11-23","cited_by_count":724},{"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":"1812.11788","title":"PVNet: Pixel-wise Voting Network for 6DoF Pose Estimation","created":"2018-12-31","cited_by_count":385},{"id":"2012.05877","title":"INeRF: Inverting Neural Radiance Fields for Pose Estimation","created":"2020-12-10","cited_by_count":382},{"id":"1901.04780","title":"DenseFusion: 6D Object Pose Estimation by Iterative Dense Fusion","created":"2019-01-15","cited_by_count":355},{"id":"2008.08465","title":"CosyPose: Consistent multi-view multi-object 6D pose estimation","created":"2020-08-19","cited_by_count":287},{"id":"1804.00175","title":"DeepIM: Deep Iterative Matching for 6D Pose Estimation","created":"2018-03-31","cited_by_count":283},{"id":"2103.10455","title":"3D Human Pose Estimation with Spatial and Temporal Transformers","created":"2021-03-18","cited_by_count":272},{"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":"1809.10790","title":"Deep Object Pose Estimation for Semantic Robotic Grasping of Household Objects","created":"2018-09-27","cited_by_count":241},{"id":"1703.10896","title":"BB8: A Scalable, Accurate, Robust to Partial Occlusion Method for Predicting the 3D Poses of Challenging Objects without Using Depth","created":"2017-03-31","cited_by_count":225},{"id":"2006.16934","title":"ERNIE-ViL: Knowledge Enhanced Vision-Language Representations Through Scene Graph","created":"2020-06-30","cited_by_count":211},{"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":"1711.08848","title":"Real-Time Seamless Single Shot 6D Object Pose Prediction","created":"2017-11-24","cited_by_count":210},{"id":"2106.02036","title":"Anticipative Video Transformer","created":"2021-06-03","cited_by_count":200},{"id":"1902.11020","title":"DPOD: 6D Pose Object Detector and Refiner","created":"2019-02-28","cited_by_count":189},{"id":"2205.12257","title":"OnePose: One-Shot Object Pose Estimation without CAD Models","created":"2022-05-24","cited_by_count":157},{"id":"2111.12707","title":"MHFormer: Multi-Hypothesis Transformer for 3D Human Pose Estimation","created":"2021-11-24","cited_by_count":151},{"id":"1511.06432","title":"Delving Deeper into Convolutional Networks for Learning Video Representations","created":"2015-11-19","cited_by_count":148},{"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":"2103.07054","title":"FS-Net: Fast Shape-based Network for Category-Level 6D Object Pose Estimation with Decoupled Rotation Mechanism","created":"2021-03-12","cited_by_count":121},{"id":"2001.01869","title":"HybridPose: 6D Object Pose Estimation under Hybrid Representations","created":"2020-01-07","cited_by_count":107},{"id":"1812.02541","title":"Segmentation-driven 6D Object Pose Estimation","created":"2018-12-06","cited_by_count":104},{"id":"1905.09304","title":"PoseRBPF: A Rao-Blackwellized Particle Filter for 6D Object Pose Tracking","created":"2019-05-22","cited_by_count":91},{"id":"2007.13866","title":"se(3)-TrackNet: Data-driven 6D Pose Tracking by Calibrating Image Residuals in Synthetic Domains","created":"2020-07-27","cited_by_count":90},{"id":"1703.04670","title":"6-DoF Object Pose from Semantic Keypoints","created":"2017-03-14","cited_by_count":89},{"id":"2108.00516","title":"BundleTrack: 6D Pose Tracking for Novel Objects without Instance or Category-Level 3D Models","created":"2021-08-01","cited_by_count":87},{"id":"2104.00633","title":"RePOSE: Fast 6D Object Pose Refinement via Deep Texture Rendering","created":"2021-04-01","cited_by_count":63},{"id":"1411.6067","title":"Viewpoints and Keypoints","created":"2014-11-22","cited_by_count":59},{"id":"1803.08103","title":"A Unified Framework for Multi-View Multi-Class Object Pose Estimation","created":"2018-03-21","cited_by_count":49},{"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":"2103.15320","title":"TFPose: Direct Human Pose Estimation with Transformers","created":"2021-03-29","cited_by_count":42},{"id":"1912.05604","title":"A Billion Ways to Grasp: An Evaluation of Grasp Sampling Schemes on a Dense, Physics-based Grasp Data Set","created":"2019-12-11","cited_by_count":30},{"id":"1508.04546","title":"Learning Analysis-by-Synthesis for 6D Pose Estimation in RGB-D Images","created":"2015-08-19","cited_by_count":29},{"id":"2209.05624","title":"Robust Category-Level 6D Pose Estimation with Coarse-to-Fine Rendering of Neural Features","created":"2022-09-12","cited_by_count":23},{"id":"2205.02536","title":"YOLOPose: Transformer-based Multi-Object 6D Pose Estimation using Keypoint Regression","created":"2022-05-05","cited_by_count":17},{"id":"2109.10948","title":"T6D-Direct: Transformers for Multi-Object 6D Pose Direct Regression","created":"2021-09-22","cited_by_count":16},{"id":"1809.06893","title":"SilhoNet: An RGB Method for 6D Object Pose Estimation","created":"2018-09-18","cited_by_count":14},{"id":"1811.08588","title":"Real-Time 6D Object Pose Estimation on CPU","created":"2018-11-21","cited_by_count":7},{"id":"2112.04981","title":"PE-former: Pose Estimation Transformer","created":"2021-12-09","cited_by_count":7},{"id":"2209.02431","title":"DPIT: Dual-Pipeline Integrated Transformer for Human Pose Estimation","created":"2022-09-02","cited_by_count":3}],"next_cursor":null}