Papers with Code 아카이브

Human Mesh Recovery

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평가표

1

보존된 평가 기록

3

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/yw0208/STAF

공식 코드

STAF: 3D Human Mesh Recovery from Video with Spatio-Temporal Alignment Fusion

https://github.com/yw0208/W-HMR

공식 코드

W-HMR: Monocular Human Mesh Recovery in World Space with Weak-Supervised Calibration

https://github.com/zczcwh/gtrs

공식 코드

A Lightweight Graph Transformer Network for Human Mesh Reconstruction from 2D Human Pose

https://github.com/zhitengli/bidrn

공식 코드

BinaryHPE: 3D Human Pose and Shape Estimation via Binarization

https://github.com/zzweng/dapa_release

공식 코드

Domain Adaptive 3D Pose Augmentation for In-the-wild Human Mesh Recovery

https://github.com/zzweng/diffusion_hpc

공식 코드

Diffusion-HPC: Synthetic Data Generation for Human Mesh Recovery in Challenging Domains

https://github.com/0jason000/CLIFF

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

https://github.com/2023-MindSpore-1/ms-code-27

End-to-end Recovery of Human Shape and Pose

https://github.com/2023-MindSpore-1/ms-code-6/tree/main/CLIFF

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

https://github.com/2023-MindSpore-4/Code-5/tree/main/HMR

End-to-end Recovery of Human Shape and Pose

https://github.com/2023-MindSpore-4/Code8/tree/main/CLIFF

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

https://github.com/2024-MindSpore-1/Code7/tree/main/CLIFF

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

https://github.com/2024-MindSpore-1/Code9/tree/main/LOGO--Mindspore-master

FLAG3D: A 3D Fitness Activity Dataset with Language Instruction

https://github.com/Droliven/pymaf_reimplementation

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

https://github.com/JDAI-CV/DSD-SATN

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

https://github.com/Liuxiang0358/HMR

End-to-end Recovery of Human Shape and Pose

https://github.com/MandyMo/pytorch_HMR

End-to-end Recovery of Human Shape and Pose

https://github.com/ManifoldFR/recvis-project

End-to-end Recovery of Human Shape and Pose

https://github.com/Mind23-2/MindCode-3/tree/main/HMR

LiDAR-HMR: 3D Human Mesh Recovery from LiDAR

https://github.com/MindSpore-paper-code-3/code4/tree/main/HMR

End-to-end Recovery of Human Shape and Pose

https://github.com/akanazawa/hmr

End-to-end Recovery of Human Shape and Pose

https://github.com/anilarmagan/HANDS19-Challenge-Toolbox

End-to-end Recovery of Human Shape and Pose

https://github.com/naver/posebert

Leveraging MoCap Data for Human Mesh Recovery

https://github.com/open-mmlab/mmpose

End-to-end Recovery of Human Shape and Pose

https://github.com/russoale/hmr2.0

End-to-end Recovery of Human Shape and Pose

https://github.com/securade/hub

ARTS: Semi-Analytical Regressor using Disentangled Skeletal Representations for Human Mesh Recovery from Videos

https://github.com/xiuyu0000/new_papers_codes/tree/main/CLIFF

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

https://github.com/yufu-wang/PromptHMR

PromptHMR: Promptable Human Mesh Recovery

https://github.com/zczcwh/potter

POTTER: Pooling Attention Transformer for Efficient Human Mesh Recovery

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.