Papers with Code 아카이브

3D Hand Pose Estimation

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

2

평가표

7

보존된 평가 기록

97

코드

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

https://github.com/vchoutas/expose

공식 코드

Monocular Expressive Body Regression through Body-Driven Attention

https://github.com/wenbowen123/catgrasp

공식 코드

CaTGrasp: Learning Category-Level Task-Relevant Grasping in Clutter from Simulation

https://github.com/wholebody3d/wholebody3d

공식 코드

H3WB: Human3.6M 3D WholeBody Dataset and Benchmark

https://github.com/wiktormucha/SHARP

공식 코드

SHARP: Segmentation of Hands and Arms by Range using Pseudo-Depth for Enhanced Egocentric 3D Hand Pose Estimation and Action Recognition

https://github.com/yihui-he/epipolar-transformers

공식 코드

Epipolar Transformers

https://github.com/zc-alexfan/digit-interacting

공식 코드

Learning to Disambiguate Strongly Interacting Hands via Probabilistic Per-pixel Part Segmentation

https://github.com/zhehengjianglancaster/amvur

공식 코드

A Probabilistic Attention Model with Occlusion-aware Texture Regression for 3D Hand Reconstruction from a Single RGB Image

https://github.com/zxz267/HaMuCo

공식 코드

HaMuCo: Hand Pose Estimation via Multiview Collaborative Self-Supervised Learning

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

End-to-end Recovery of Human Shape and Pose

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

End-to-end Recovery of Human Shape and Pose

https://github.com/2024-MindSpore-1/Code2/tree/main/model-1/graphormer

Mesh Graphormer

https://github.com/3d-hand-shape/hand-graph-cnn

3D Hand Shape and Pose Estimation from a Single RGB Image

https://github.com/674106399/JointBoneLoss

Weakly-Supervised Mesh-Convolutional Hand Reconstruction in the Wild

https://github.com/ArashHosseini/hand-graph-cnn-gpu

3D Hand Shape and Pose Estimation from a Single RGB Image

https://github.com/Chenzhoujia/190916-hand3d-CNN-GNN

Learning to Estimate 3D Hand Pose from Single RGB Images

https://github.com/EAST-J/Youtubehand

Weakly-Supervised Mesh-Convolutional Hand Reconstruction in the Wild

https://github.com/LawrenceZ22/ThermoHands

ThermoHands: A Benchmark for 3D Hand Pose Estimation from Egocentric Thermal Images

https://github.com/Liuxiang0358/HMR

End-to-end Recovery of Human Shape and Pose

https://github.com/MS-P3/code5/tree/main/graphormer

Mesh Graphormer

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/MindCode-4/code-1/tree/main/vit_hybrid

FastViT: A Fast Hybrid Vision Transformer using Structural Reparameterization

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

End-to-end Recovery of Human Shape and Pose

https://github.com/NVlabs/6dof-graspnet

6-DOF GraspNet: Variational Grasp Generation for Object Manipulation

https://github.com/Neilblaze/Aerowave

V2V-PoseNet: Voxel-to-Voxel Prediction Network for Accurate 3D Hand and Human Pose Estimation from a Single Depth Map

https://github.com/RonLek/FastV2C-HandNet

DeepPrior++: Improving Fast and Accurate 3D Hand Pose Estimation

https://github.com/Wavelet303/HAMR

End-to-end Hand Mesh Recovery from a Monocular RGB Image

https://github.com/YangYangTaoTao/V2V-PoseNet_Pytorch

V2V-PoseNet: Voxel-to-Voxel Prediction Network for Accurate 3D Hand and Human Pose Estimation from a Single Depth Map

https://github.com/ajdillhoff/colorhandpose3d-pytorch

Learning to Estimate 3D Hand Pose from Single RGB Images

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/balala8/FastViT_pytorch

FastViT: A Fast Hybrid Vision Transformer using Structural Reparameterization

https://github.com/bnestor/second-hand-rl

Learning to Estimate 3D Hand Pose from Single RGB Images

https://github.com/boukhayma/3dhand

3D Hand Shape and Pose from Images in the Wild

https://github.com/dragonbook/V2V-PoseNet-pytorch

V2V-PoseNet: Voxel-to-Voxel Prediction Network for Accurate 3D Hand and Human Pose Estimation from a Single Depth Map

https://github.com/dumyy/handpose

DeepPrior++: Improving Fast and Accurate 3D Hand Pose Estimation

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