Human Mesh Recovery

48 papers with code • 1 benchmarks • 3 datasets

Estimate 3D body mesh from images

Most implemented papers

End-to-end Recovery of Human Shape and Pose

open-mmlab/mmpose CVPR 2018

The main objective is to minimize the reprojection loss of keypoints, which allow our model to be trained using images in-the-wild that only have ground truth 2D annotations.

CLIFF: Carrying Location Information in Full Frames into Human Pose and Shape Estimation

huawei-noah/noah-research 1 Aug 2022

Top-down methods dominate the field of 3D human pose and shape estimation, because they are decoupled from human detection and allow researchers to focus on the core problem.

Human Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation

Arthur151/DSD-SATN ICCV 2019

Different from the existing methods try to obtain all the complex 3D pose, shape, and camera parameters from one coupling feature, we propose a skeleton-disentangling based framework, which divides this task into multi-level spatial and temporal granularity in a decoupling manner.

PyMAF: 3D Human Pose and Shape Regression with Pyramidal Mesh Alignment Feedback Loop

HongwenZhang/PyMAF ICCV 2021

Regression-based methods have recently shown promising results in reconstructing human meshes from monocular images.

LiDAR-HMR: 3D Human Mesh Recovery from LiDAR

soullessrobot/lidar-hmr 20 Nov 2023

In recent years, point cloud perception tasks have been garnering increasing attention.

Hulk: A Universal Knowledge Translator for Human-Centric Tasks

opengvlab/humanbench 4 Dec 2023

Human-centric perception tasks, e. g., pedestrian detection, skeleton-based action recognition, and pose estimation, have wide industrial applications, such as metaverse and sports analysis.

Learning 3D Human Shape and Pose from Dense Body Parts

HongwenZhang/DaNet-DensePose2SMPL 31 Dec 2019

Reconstructing 3D human shape and pose from monocular images is challenging despite the promising results achieved by the most recent learning-based methods.

Human Mesh Recovery from Multiple Shots

geopavlakos/multishot CVPR 2022

The tools we develop open the door to processing and analyzing in 3D content from a large library of edited media, which could be helpful for many downstream applications.

Self-supervised 3D Human Mesh Recovery from Noisy Point Clouds

wangsen1312/unsupervised3dhuman 15 Jul 2021

However, Chamfer distance is quite sensitive to noise and outliers, thus could be unreliable to assign correspondences.

Probabilistic Modeling for Human Mesh Recovery

nkolot/ProHMR ICCV 2021

This paper focuses on the problem of 3D human reconstruction from 2D evidence.