3D Human Pose Estimation

3D Human Pose Estimation is a computer vision task that involves estimating the 3D positions and orientations of body joints and bones from 2D images or videos. The goal is to reconstruct the 3D pose of a person in real-time, which can be used in a variety of applications, such as virtual reality, human-computer interaction, and motion analysis.

Papers

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Showing 621–630 of 665 papers

Title	Date	Tasks	Status
Learnable Triangulation of Human Pose	May 14, 2019	3D Human Pose EstimationMulti-view 3D Human Pose Estimation	CodeCode Available
Camera Motion Agnostic 3D Human Pose Estimation	Dec 1, 2021	3D human pose and shape estimation3D Human Pose Estimation	CodeCode Available
Generating Multiple Hypotheses for 3D Human Pose Estimation with Mixture Density Network	Apr 11, 2019	3D Human Pose EstimationMonocular 3D Human Pose Estimation	CodeCode Available
PoseGRAF: Geometric-Reinforced Adaptive Fusion for Monocular 3D Human Pose Estimation	Jun 17, 2025	3D Human Pose Estimation3D Pose Estimation	CodeCode Available
Vision-based Control of a Quadrotor in User Proximity: Mediated vs End-to-End Learning Approaches	Sep 24, 2018	3D Human Pose EstimationState Estimation	CodeCode Available
Camera Distance-aware Top-down Approach for 3D Multi-person Pose Estimation from a Single RGB Image	Jul 26, 2019	3D Absolute Human Pose Estimation3D Depth Estimation	CodeCode Available
VNect: Real-time 3D Human Pose Estimation with a Single RGB Camera	May 3, 2017	3D Human Pose EstimationPose Estimation	CodeCode Available
Generalizing Monocular 3D Human Pose Estimation in the Wild	Apr 11, 2019	3D Human Pose Estimation3D Pose Estimation	CodeCode Available
Flexible graph convolutional network for 3D human pose estimation	Jul 26, 2024	3D Human Pose EstimationPose Estimation	CodeCode Available
Sparseness Meets Deepness: 3D Human Pose Estimation from Monocular Video	Nov 30, 2015	2D Pose Estimation3D Human Pose Estimation	CodeCode Available

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All datasets 3DPW MPI-INF-3DHP Human3.6M HumanEva-I H3WB Total Capture EMDB AGORA Panoptic Surreal 3D Poses in the Wild Challenge AIST++

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	Simple-baseline	PA-MPJPE	157	—	Unverified
2	HMR	MPJPE	130	—	Unverified
3	BMP	MPVPE	119.3	—	Unverified
4	SPIN	MPVPE	116.4	—	Unverified
5	Wenshuo et a;.	MPVPE	112.6	—	Unverified
6	TCMR (T=16 w/o 3DPW)	MPVPE	111.5	—	Unverified
7	CHOMP	MPVPE	110.1	—	Unverified
8	PC-HMR	MPVPE	108.6	—	Unverified
9	3DCrowdNet	MPVPE	108.5	—	Unverified
10	SMPLify	PA-MPJPE	106.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	VNect (Augm.)	MPJPE	124.7	—	Unverified
2	HMR	MPJPE	124.2	—	Unverified
3	Single-Shot Multi-Person	MPJPE	122.2	—	Unverified
4	Mehta	MPJPE	117.6	—	Unverified
5	PONet	MPJPE	115	—	Unverified
6	Pose Consensus (monocular)	MPJPE	112.1	—	Unverified
7	GeoRep (fully-supervised)	MPJPE	110.8	—	Unverified
8	XFormer (HRNet)	MPJPE	109.8	—	Unverified
9	EpipolarPose (fully-supervised)	MPJPE	108.99	—	Unverified
10	SPIN	MPJPE	105.2	—	Unverified