3D Multi-Person Pose Estimation Edit Task
Computer Vision • 3D Human Pose Estimation
About
This task aims to solve root-relative 3D multi-person pose estimation. No human bounding box and root joint coordinate groundtruth are used in testing time.
( Image credit: RootNet )
Benchmarks
| TREND | DATASET | BEST METHOD | PAPER TITLE | PAPER | CODE | COMPARE |
|---|---|---|---|---|---|---|
|
||||||
|
||||||
|
||||||
|
Subtasks
Datasets
Greatest papers with code
Camera Distance-aware Top-down Approach for 3D Multi-person Pose Estimation from a Single RGB Image
ICCV 2019
• mks0601/3DMPPE_POSENET_RELEASE
• 
Although significant improvement has been achieved recently in 3D human pose estimation, most of the previous methods only treat a single-person case.
Ranked #2 on
Root Joint Localization
on Human3.6M
3D ABSOLUTE HUMAN POSE ESTIMATION 3D MULTI-PERSON POSE ESTIMATION (ABSOLUTE) 3D MULTI-PERSON POSE ESTIMATION (ROOT-RELATIVE) MONOCULAR 3D HUMAN POSE ESTIMATION MULTI-PERSON POSE ESTIMATION ROOT JOINT LOCALIZATION
Fast and Robust Multi-Person 3D Pose Estimation from Multiple Views
This paper addresses the problem of 3D pose estimation for multiple people in a few calibrated camera views.
Ranked #2 on
3D Multi-Person Pose Estimation
on Shelf
Monocular, One-stage, Regression of Multiple 3D People
Through a body-center-guided sampling process, the body mesh parameters of all people in the image can be easily extracted from the Mesh Parameter map.
Ranked #1 on
3D Human Pose Estimation
on 3DPW
(using extra training data)
VoxelPose: Towards Multi-Camera 3D Human Pose Estimation in Wild Environment
ECCV 2020
• microsoft/voxelpose-pytorch
•
In contrast to the previous efforts which require to establish cross-view correspondence based on noisy and incomplete 2D pose estimations, we present an end-to-end solution which directly operates in the $3$D space, therefore avoids making incorrect decisions in the 2D space.
Ranked #1 on
3D Multi-Person Pose Estimation
on Campus
Cross-View Tracking for Multi-Human 3D Pose Estimation at over 100 FPS
To further verify the scalability of our method, we propose a new large-scale multi-human dataset with 12 to 28 camera views.
Ranked #2 on
3D Multi-Person Pose Estimation
on Campus
Graph and Temporal Convolutional Networks for 3D Multi-person Pose Estimation in Monocular Videos
• 3dpose/GnTCN
•
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.
3D ABSOLUTE HUMAN POSE ESTIMATION 3D MULTI-PERSON POSE ESTIMATION (ABSOLUTE) 3D MULTI-PERSON POSE ESTIMATION (ROOT-RELATIVE) 3D POSE ESTIMATION MONOCULAR 3D HUMAN POSE ESTIMATION MULTI-PERSON POSE ESTIMATION ROOT JOINT LOCALIZATION
Temporal Smoothing for 3D Human Pose Estimation and Localization for Occluded People
In multi-person pose estimation actors can be heavily occluded, even become fully invisible behind another person.
Ranked #1 on
3D Multi-Person Pose Estimation
on MuPoTS-3D
3D MULTI-PERSON POSE ESTIMATION (ROOT-RELATIVE) MULTI-PERSON POSE ESTIMATION
Monocular 3D Multi-Person Pose Estimation by Integrating Top-Down and Bottom-Up Networks
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.
3D MULTI-PERSON POSE ESTIMATION HUMAN DETECTION MULTI-PERSON POSE ESTIMATION