paper-with-me

Papers

Graph-Based 3D Multi-Person Pose Estimation Using Multi-View Images

2021-09-13 · ICCV 2021 10 · Size Wu, Sheng Jin, Wentao Liu, Lei Bai, Chen Qian, Dong Liu, Wanli Ouyang

This paper studies the task of estimating the 3D human poses of multiple persons from multiple calibrated camera views. Following the top-down paradigm, we decompose the task into two stages, i.e. person localization and pose estimation. Both stages are processed in coarse-to-fine manners. And we propose three task-specific graph neural networks for effective message passing. For 3D person localization, we first use Multi-view Matching Graph Module (MMG) to learn the cross-view association and recover coarse human proposals. The Center Refinement Graph Module (CRG) further refines the results via flexible point-based prediction. For 3D pose estimation, the Pose Regression Graph Module (PRG) learns both the multi-view geometry and structural relations between human joints. Our approach achieves state-of-the-art performance on CMU Panoptic and Shelf datasets with significantly lower computation complexity.

📄 PDF Abstract BibTeX arXiv:2109.05885

Code (1)

wusize/multiview_pose 공식 구현 pytorch

Tasks

3D Multi-Person Pose Estimation3D Pose EstimationMulti-Person Pose EstimationPose Estimation

Similar Papers 제목 키워드 기반

PoseTrack: Joint Multi-Person Pose Estimation and Tracking

2016-11-23 · CVPR 2017 7 · Umar Iqbal, Anton Milan, Juergen Gall

In this work, we introduce the challenging problem of joint multi-person pose estimation and tracking of an unknown number of persons in unconstrained videos. Existing methods for multi-person pose estimation in images c…

Multi-Person Pose EstimationMulti-Person Pose Estimation and TrackingPose EstimationPose Tracking

Differentiable Hierarchical Graph Grouping for Multi-Person Pose Estimation

2020-07-23 · ECCV 2020 8 · Sheng Jin, Wentao Liu, Enze Xie, Wenhai Wang 외

Multi-person pose estimation is challenging because it localizes body keypoints for multiple persons simultaneously. Previous methods can be divided into two streams, i.e. top-down and bottom-up methods. The top-down met…

2D Human Pose EstimationClusteringGraph ClusteringGraph Neural Network+4

Multi-Person Pose Estimation with Local Joint-to-Person Associations

2016-08-30 · Umar Iqbal, Juergen Gall

Despite of the recent success of neural networks for human pose estimation, current approaches are limited to pose estimation of a single person and cannot handle humans in groups or crowds. In this work, we propose a me…

Keypoint DetectionMulti-Person Pose EstimationOutlier DetectionPose Estimation

FOSS: Multi-Person Age Estimation with Focusing on Objects and Still Seeing Surroundings

2020-10-15 · Masakazu Yoshimura, Satoshi Ogata

Age estimation from images can be used in many practical scenes. Most of the previous works targeted on the estimation from images in which only one face exists. Also, most of the open datasets for age estimation contain…

Age Estimation

Graph and Temporal Convolutional Networks for 3D Multi-person Pose Estimation in Monocular Videos

2020-12-22 · Yu Cheng, Bo wang, Bo Yang, Robby T. Tan

Despite the recent progress, 3D multi-person pose estimation from monocular videos is still challenging due to the commonly encountered problem of missing information caused by occlusion, partially out-of-frame target pe…

3D Absolute Human Pose Estimation3D Human Pose Estimation3D Multi-Person Pose Estimation3D Multi-Person Pose Estimation (absolute)+6