{"list":"other","total":51,"rows":[{"id":"1512.03385","title":"Deep Residual Learning for Image Recognition","created":"2015-12-10","cited_by_count":52096},{"id":"1405.0312","title":"Microsoft COCO: Common Objects in Context","created":"2014-05-01","cited_by_count":17608},{"id":"1703.06870","title":"Mask R-CNN","created":"2017-03-20","cited_by_count":7277},{"id":"1611.07004","title":"Image-to-Image Translation with Conditional Adversarial Networks","created":"2016-11-21","cited_by_count":4527},{"id":"1505.07818","title":"Domain-Adversarial Training of Neural Networks","created":"2015-05-28","cited_by_count":3044},{"id":"1502.02791","title":"Learning Transferable Features with Deep Adaptation Networks","created":"2015-02-10","cited_by_count":1329},{"id":"1702.05464","title":"Adversarial Discriminative Domain Adaptation","created":"2017-02-17","cited_by_count":1311},{"id":"1708.04896","title":"Random Erasing Data Augmentation","created":"2017-08-16","cited_by_count":1239},{"id":"1607.01719","title":"Deep CORAL: Correlation Alignment for Deep Domain Adaptation","created":"2016-07-06","cited_by_count":1200},{"id":"1711.03213","title":"CyCADA: Cycle-Consistent Adversarial Domain Adaptation","created":"2017-11-08","cited_by_count":1082},{"id":"1603.06937","title":"Stacked Hourglass Networks for Human Pose Estimation","created":"2016-03-22","cited_by_count":915},{"id":"1607.08128","title":"Keep it SMPL: Automatic Estimation of 3D Human Pose and Shape from a Single Image","created":"2016-07-27","cited_by_count":695},{"id":"1811.12833","title":"ADVENT: Adversarial Entropy Minimization for Domain Adaptation in Semantic Segmentation","created":"2018-11-30","cited_by_count":623},{"id":"1412.3474","title":"Deep Domain Confusion: Maximizing for Domain Invariance","created":"2014-12-10","cited_by_count":600},{"id":"1611.09813","title":"Monocular 3D Human Pose Estimation In The Wild Using Improved CNN Supervision","created":"2016-11-29","cited_by_count":494},{"id":"1803.03243","title":"Domain Adaptive Faster R-CNN for Object Detection in the Wild","created":"2018-03-08","cited_by_count":443},{"id":"1811.11742","title":"3D human pose estimation in video with temporal convolutions and semi-supervised training","created":"2018-11-28","cited_by_count":403},{"id":"1705.03098","title":"A simple yet effective baseline for 3d human pose estimation","created":"2017-05-08","cited_by_count":401},{"id":"1701.01370","title":"Learning from Synthetic Humans","created":"2017-01-05","cited_by_count":359},{"id":"1809.09478","title":"Taking A Closer Look at Domain Shift: Category-level Adversaries for Semantics Consistent Domain Adaptation","created":"2018-09-25","cited_by_count":295},{"id":"1711.08229","title":"Integral Human Pose Regression","created":"2017-11-22","cited_by_count":256},{"id":"1510.02192","title":"Simultaneous Deep Transfer Across Domains and Tasks","created":"2015-10-08","cited_by_count":206},{"id":"1701.02468","title":"Unite the People: Closing the Loop Between 3D and 2D Human Representations","created":"2017-01-10","cited_by_count":205},{"id":"1712.03453","title":"Single-Shot Multi-Person 3D Pose Estimation From Monocular RGB","created":"2017-12-09","cited_by_count":195},{"id":"1903.03303","title":"Learning from Synthetic Data for Crowd Counting in the Wild","created":"2019-03-08","cited_by_count":148},{"id":"1907.11346","title":"Camera Distance-aware Top-down Approach for 3D Multi-person Pose Estimation from a Single RGB Image","created":"2019-07-26","cited_by_count":132},{"id":"1704.00159","title":"Compositional Human Pose Regression","created":"2017-04-01","cited_by_count":124},{"id":"1704.02447","title":"Towards 3D Human Pose Estimation in the Wild: a Weakly-supervised Approach","created":"2017-04-08","cited_by_count":115},{"id":"1612.06524","title":"3D Human Pose Estimation = 2D Pose Estimation + Matching","created":"2016-12-20","cited_by_count":113},{"id":"1903.02330","title":"Self-Supervised Learning of 3D Human Pose using Multi-view Geometry","created":"2019-03-06","cited_by_count":98},{"id":"1904.04812","title":"Unsupervised 3D Pose Estimation with Geometric Self-Supervision","created":"2019-04-09","cited_by_count":95},{"id":"1803.00455","title":"LCR-Net++: Multi-person 2D and 3D Pose Detection in Natural Images","created":"2018-03-01","cited_by_count":88},{"id":"1803.09722","title":"3D Human Pose Estimation in the Wild by Adversarial Learning","created":"2018-03-26","cited_by_count":86},{"id":"2003.10275","title":"Cross-domain Object Detection through Coarse-to-Fine Feature Adaptation","created":"2020-03-23","cited_by_count":82},{"id":"2006.07778","title":"Cascaded deep monocular 3D human pose estimation with evolutionary training data","created":"2020-06-14","cited_by_count":80},{"id":"1611.09010","title":"3D Human Pose Estimation from a Single Image via Distance Matrix Regression","created":"2016-11-28","cited_by_count":73},{"id":"1701.00295","title":"Lifting from the Deep: Convolutional 3D Pose Estimation from a Single Image","created":"2017-01-01","cited_by_count":73},{"id":"2003.07581","title":"Weakly-Supervised 3D Human Pose Learning via Multi-view Images in the Wild","created":"2020-03-17","cited_by_count":66},{"id":"2004.02186","title":"Lightweight Multi-View 3D Pose Estimation through Camera-Disentangled Representation","created":"2020-04-05","cited_by_count":57},{"id":"1604.02703","title":"Synthesizing Training Images for Boosting Human 3D Pose Estimation","created":"2016-04-10","cited_by_count":52},{"id":"1701.02354","title":"MonoCap: Monocular Human Motion Capture using a CNN Coupled with a Geometric Prior","created":"2017-01-09","cited_by_count":36},{"id":"1702.02258","title":"Generating Multiple Diverse Hypotheses for Human 3D Pose Consistent with 2D Joint Detections","created":"2017-02-08","cited_by_count":30},{"id":"1906.01314","title":"Example-Guided Style Consistent Image Synthesis from Semantic Labeling","created":"2019-06-04","cited_by_count":29},{"id":"1701.08985","title":"Deep Multitask Architecture for Integrated 2D and 3D Human Sensing","created":"2017-01-31","cited_by_count":21},{"id":"1509.04309","title":"Sparse Representation for 3D Shape Estimation: A Convex Relaxation Approach","created":"2015-09-14","cited_by_count":16},{"id":"1704.03039","title":"Semantically Consistent Regularization for Zero-Shot Recognition","created":"2017-04-10","cited_by_count":14},{"id":"1802.00285","title":"Virtual-to-Real: Learning to Control in Visual Semantic Segmentation","created":"2018-02-01","cited_by_count":12},{"id":"1411.2942","title":"3D Shape Estimation from 2D Landmarks: A Convex Relaxation Approach","created":"2014-11-11","cited_by_count":11},{"id":"1509.06720","title":"A Dual-Source Approach for 3D Pose Estimation from a Single Image","created":"2015-09-22","cited_by_count":9},{"id":"1507.05578","title":"Subspace Alignment Based Domain Adaptation for RCNN Detector","created":"2015-07-20","cited_by_count":6},{"id":"1808.02595","title":"A Semi-Supervised Data Augmentation Approach using 3D Graphical Engines","created":"2018-08-08","cited_by_count":5}],"next_cursor":null}