3D Multi-Person Pose Estimation (root-relative)

11 papers with code • 1 benchmarks • 1 datasets

This task aims to solve root-relative 3D multi-person pose estimation (person-centric coordinate system). No ground truth human bounding box and human root joint coordinates are used during testing stage.

( Image credit: RootNet )


Most implemented papers

Towards 3D Human Pose Estimation in the Wild: a Weakly-supervised Approach

xingyizhou/pose-hg-3d ICCV 2017

We propose a weakly-supervised transfer learning method that uses mixed 2D and 3D labels in a unified deep neutral network that presents two-stage cascaded structure.

Single-Shot Multi-Person 3D Pose Estimation From Monocular RGB

Daniil-Osokin/lightweight-human-pose-estimation-3d-demo.pytorch 9 Dec 2017

Our approach uses novel occlusion-robust pose-maps (ORPM) which enable full body pose inference even under strong partial occlusions by other people and objects in the scene.

Camera Distance-aware Top-down Approach for 3D Multi-person Pose Estimation from a Single RGB Image


Although significant improvement has been achieved recently in 3D human pose estimation, most of the previous methods only treat a single-person case.

Multi-Person Absolute 3D Human Pose Estimation with Weak Depth Supervision

vegesm/wdspose 8 Apr 2020

In 3D human pose estimation one of the biggest problems is the lack of large, diverse datasets.

HDNet: Human Depth Estimation for Multi-Person Camera-Space Localization

jiahaoLjh/HumanDepth ECCV 2020

Current works on multi-person 3D pose estimation mainly focus on the estimation of the 3D joint locations relative to the root joint and ignore the absolute locations of each pose.

SMAP: Single-Shot Multi-Person Absolute 3D Pose Estimation

zju3dv/smap ECCV 2020

Recovering multi-person 3D poses with absolute scales from a single RGB image is a challenging problem due to the inherent depth and scale ambiguity from a single view.

Temporal Smoothing for 3D Human Pose Estimation and Localization for Occluded People

vegesm/pose_refinement 31 Oct 2020

In multi-person pose estimation actors can be heavily occluded, even become fully invisible behind another person.

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

3dpose/GnTCN 22 Dec 2020

To tackle this problem, we propose a novel framework integrating graph convolutional networks (GCNs) and temporal convolutional networks (TCNs) to robustly estimate camera-centric multi-person 3D poses that do not require camera parameters.

Monocular 3D Multi-Person Pose Estimation by Integrating Top-Down and Bottom-Up Networks

3dpose/3D-Multi-Person-Pose CVPR 2021

Besides the integration of top-down and bottom-up networks, unlike existing pose discriminators that are designed solely for single person, and consequently cannot assess natural inter-person interactions, we propose a two-person pose discriminator that enforces natural two-person interactions.

Distribution-Aware Single-Stage Models for Multi-Person 3D Pose Estimation

wangzt-halo/das CVPR 2022

In this paper, we present a novel Distribution-Aware Single-stage (DAS) model for tackling the challenging multi-person 3D pose estimation problem.