{"list":"other","total":52,"rows":[{"id":"1911.05722","title":"Momentum Contrast for Unsupervised Visual Representation Learning","created":"2019-11-13","cited_by_count":7513},{"id":"1703.06870","title":"Mask R-CNN","created":"2017-03-20","cited_by_count":7277},{"id":"2006.07733","title":"Bootstrap your own latent: A new approach to self-supervised Learning","created":"2020-06-13","cited_by_count":4750},{"id":"2003.12039","title":"RAFT: Recurrent All-Pairs Field Transforms for Optical Flow","created":"2020-03-26","cited_by_count":2415},{"id":"2001.07685","title":"FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence","created":"2020-01-21","cited_by_count":2085},{"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":"2110.08263","title":"FlexMatch: Boosting Semi-Supervised Learning with Curriculum Pseudo Labeling","created":"2021-10-15","cited_by_count":540},{"id":"1711.07566","title":"Neural 3D Mesh Renderer","created":"2017-11-20","cited_by_count":437},{"id":"1904.01786","title":"Soft Rasterizer: A Differentiable Renderer for Image-based 3D Reasoning","created":"2019-04-03","cited_by_count":420},{"id":"1812.11788","title":"PVNet: Pixel-wise Voting Network for 6DoF Pose Estimation","created":"2018-12-31","cited_by_count":385},{"id":"2106.09018","title":"End-to-End Semi-Supervised Object Detection with Soft Teacher","created":"2021-06-16","cited_by_count":316},{"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":"1808.08319","title":"BOP: Benchmark for 6D Object Pose Estimation","created":"2018-08-24","cited_by_count":254},{"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":"1908.07433","title":"Pix2Pose: Pixel-Wise Coordinate Regression of Objects for 6D Pose Estimation","created":"2019-08-20","cited_by_count":218},{"id":"1711.07837","title":"UnFlow: Unsupervised Learning of Optical Flow with a Bidirectional Census Loss","created":"2017-11-21","cited_by_count":202},{"id":"2102.12145","title":"GDRNPP: A Geometry-guided and Fully Learning-based Object Pose Estimator","created":"2021-02-24","cited_by_count":148},{"id":"1812.02781","title":"ROI-10D: Monocular Lifting of 2D Detection to 6D Pose and Metric Shape","created":"2018-12-06","cited_by_count":123},{"id":"2106.10456","title":"Humble Teachers Teach Better Students for Semi-Supervised Object Detection","created":"2021-06-19","cited_by_count":116},{"id":"2203.09418","title":"ZebraPose: Coarse to Fine Surface Encoding for 6DoF Object Pose Estimation","created":"2022-03-17","cited_by_count":116},{"id":"1812.02541","title":"Segmentation-driven 6D Object Pose Estimation","created":"2018-12-06","cited_by_count":104},{"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":"1911.08324","title":"Single-Stage 6D Object Pose Estimation","created":"2019-11-19","cited_by_count":88},{"id":"2108.08367","title":"SO-Pose: Exploiting Self-Occlusion for Direct 6D Pose Estimation","created":"2021-08-18","cited_by_count":88},{"id":"2004.06468","title":"Self6D: Self-Supervised Monocular 6D Object Pose Estimation","created":"2020-04-14","cited_by_count":79},{"id":"2303.12787","title":"EPro-PnP: Generalized End-to-End Probabilistic Perspective-n-Points for Monocular Object Pose Estimation","created":"2023-03-22","cited_by_count":79},{"id":"2105.07014","title":"SMURF: Self-Teaching Multi-Frame Unsupervised RAFT with Full-Image Warping","created":"2021-05-14","cited_by_count":74},{"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":"1909.06043","title":"End-to-End Learnable Geometric Vision by Backpropagating PnP Optimization","created":"2019-09-13","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":"2204.02078","title":"Semi-supervised Semantic Segmentation with Error Localization Network","created":"2022-04-05","cited_by_count":57},{"id":"2203.16317","title":"PseCo: Pseudo Labeling and Consistency Training for Semi-Supervised Object Detection","created":"2022-03-30","cited_by_count":51},{"id":"1803.10910","title":"Deep Unsupervised Saliency Detection: A Multiple Noisy Labeling Perspective","created":"2018-03-29","cited_by_count":50},{"id":"2204.12516","title":"Coupled Iterative Refinement for 6D Multi-Object Pose Estimation","created":"2022-04-26","cited_by_count":48},{"id":"2207.02541","title":"Dense Teacher: Dense Pseudo-Labels for Semi-supervised Object Detection","created":"2022-07-06","cited_by_count":48},{"id":"2104.00337","title":"Wide-Depth-Range 6D Object Pose Estimation in Space","created":"2021-04-01","cited_by_count":45},{"id":"2109.10115","title":"StereOBJ-1M: Large-scale Stereo Image Dataset for 6D Object Pose Estimation","created":"2021-09-21","cited_by_count":40},{"id":"2203.12870","title":"RNNPose: Recurrent 6-DoF Object Pose Refinement with Robust Correspondence Field Estimation and Pose Optimization","created":"2022-03-24","cited_by_count":38},{"id":"2203.10339","title":"Occlusion-Aware Self-Supervised Monocular 6D Object Pose Estimation","created":"2022-03-19","cited_by_count":34},{"id":"1707.04796","title":"LabelFusion: A Pipeline for Generating Ground Truth Labels for Real RGBD Data of Cluttered Scenes","created":"2017-07-15","cited_by_count":32},{"id":"2203.09836","title":"Perspective Flow Aggregation for Data-Limited 6D Object Pose Estimation","created":"2022-03-18","cited_by_count":32},{"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":"2205.01823","title":"Symmetry and Uncertainty-Aware Object SLAM for 6DoF Object Pose Estimation","created":"2022-05-04","cited_by_count":28},{"id":"2303.16235","title":"Spatiotemporal Self-supervised Learning for Point Clouds in the Wild","created":"2023-03-28","cited_by_count":23},{"id":"2208.00113","title":"Neural Correspondence Field for Object Pose Estimation","created":"2022-07-30","cited_by_count":21},{"id":"2204.07049","title":"Sim-to-Real 6D Object Pose Estimation via Iterative Self-training for Robotic Bin Picking","created":"2022-04-14","cited_by_count":20},{"id":"2208.02129","title":"SC6D: Symmetry-agnostic and Correspondence-free 6D Object Pose Estimation","created":"2022-08-03","cited_by_count":17},{"id":"2306.13266","title":"Shape-Constraint Recurrent Flow for 6D Object Pose Estimation","created":"2023-06-23","cited_by_count":17},{"id":"2104.03658","title":"DSC-PoseNet: Learning 6DoF Object Pose Estimation via Dual-scale Consistency","created":"2021-04-08","cited_by_count":14},{"id":"2303.12396","title":"Rigidity-Aware Detection for 6D Object Pose Estimation","created":"2023-03-22","cited_by_count":13},{"id":"2303.16947","title":"De-coupling and De-positioning Dense Self-supervised Learning","created":"2023-03-29","cited_by_count":3}],"next_cursor":null}