Papers with Code 아카이브

3D Human Pose Estimation

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하위 태스크: 9
평가표: 25
보존된 평가 기록: 447

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.

코드

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

https://github.com/llmpass/RSTT

공식 코드

RSTT: Real-time Spatial Temporal Transformer for Space-Time Video Super-Resolution

https://github.com/lmb-freiburg/rgbd-pose3d

공식 코드

3D Human Pose Estimation in RGBD Images for Robotic Task Learning

https://github.com/lojol2327/DiffuPose

공식 코드

DiffuPose: Monocular 3D Human Pose Estimation via Denoising Diffusion Probabilistic Model

https://github.com/longcw/crossview_3d_pose_tracking

공식 코드

Cross-View Tracking for Multi-Human 3D Pose Estimation at over 100 FPS

https://github.com/lovepiano/SMFN

공식 코드

A Single Frame and Multi-Frame Joint Network for 360-degree Panorama Video Super-Resolution

https://github.com/lovepiano/SMFN_For_360VSR

공식 코드

A Single Frame and Multi-Frame Joint Network for 360-degree Panorama Video Super-Resolution

https://github.com/lutao2021/DiMeR

공식 코드

DiMeR: Disentangled Mesh Reconstruction Model

https://github.com/malefikus/mocapdeform

공식 코드

MoCapDeform: Monocular 3D Human Motion Capture in Deformable Scenes

https://github.com/marcopesavento/Super-resolution-3D-Human-Shape-from-a-Single-Low-Resolution-Image

공식 코드

Super-resolution 3D Human Shape from a Single Low-Resolution Image

https://github.com/marikoisogawa/OpticalNLOSPose

공식 코드

Optical Non-Line-of-Sight Physics-based 3D Human Pose Estimation

https://github.com/martayang/kitro

공식 코드

KITRO: Refining Human Mesh by 2D Clues and Kinematic-tree Rotation

https://github.com/masterhow/eventpointpose

공식 코드

Efficient Human Pose Estimation via 3D Event Point Cloud

https://github.com/megvii-research/wacv2024-safa

공식 코드

Scale-Adaptive Feature Aggregation for Efficient Space-Time Video Super-Resolution

https://github.com/mehwishg/dtf

공식 코드

Enhancing 3D Human Pose Estimation Amidst Severe Occlusion with Dual Transformer Fusion

https://github.com/mfawzy/CrossFormer

공식 코드

CrossFormer: Cross Spatio-Temporal Transformer for 3D Human Pose Estimation

https://github.com/mgholamikn/AdaptPose

공식 코드

AdaptPose: Cross-Dataset Adaptation for 3D Human Pose Estimation by Learnable Motion Generation

https://github.com/michigancog/forcepose

공식 코드

Learning to Estimate External Forces of Human Motion in Video

https://github.com/microsoft/MeshTransformer

공식 코드

End-to-End Human Pose and Mesh Reconstruction with Transformers

https://github.com/microsoft/meshgraphormer

공식 코드

Mesh Graphormer

https://github.com/microsoft/multiview-human-pose-estimation-pytorch

공식 코드

Cross View Fusion for 3D Human Pose Estimation

https://github.com/microsoft/voxelpose-pytorch

공식 코드

VoxelPose: Towards Multi-Camera 3D Human Pose Estimation in Wild Environment

https://github.com/microsoft/vsr-challenge

공식 코드

ICME 2025 Grand Challenge on Video Super-Resolution for Video Conferencing

https://github.com/mkocabas/EpipolarPose

공식 코드

Self-Supervised Learning of 3D Human Pose using Multi-view Geometry

https://github.com/mkocabas/PARE

공식 코드

PARE: Part Attention Regressor for 3D Human Body Estimation

https://github.com/mkocabas/SPEC

공식 코드

SPEC: Seeing People in the Wild with an Estimated Camera

https://github.com/mkocabas/VIBE

공식 코드

VIBE: Video Inference for Human Body Pose and Shape Estimation

https://github.com/mks0601/3DMPPE_POSENET_RELEASE

공식 코드

Camera Distance-aware Top-down Approach for 3D Multi-person Pose Estimation from a Single RGB Image

https://github.com/mks0601/3DMPPE_ROOTNET_RELEASE

공식 코드

Camera Distance-aware Top-down Approach for 3D Multi-person Pose Estimation from a Single RGB Image

https://github.com/mks0601/Hand4Whole_RELEASE

공식 코드

Accurate 3D Hand Pose Estimation for Whole-Body 3D Human Mesh Estimation

https://github.com/mks0601/I2L-MeshNet_RELEASE

공식 코드

I2L-MeshNet: Image-to-Lixel Prediction Network for Accurate 3D Human Pose and Mesh Estimation from a Single RGB Image

https://github.com/mks0601/NeuralAnnot_RELEASE

공식 코드

Three Recipes for Better 3D Pseudo-GTs of 3D Human Mesh Estimation in the Wild

https://github.com/mks0601/V2V-PoseNet_RELEASE

공식 코드

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

https://github.com/mmahdavian/stpotr

공식 코드

STPOTR: Simultaneous Human Trajectory and Pose Prediction Using a Non-Autoregressive Transformer for Robot Following Ahead

https://github.com/mmlab-cv/deca

공식 코드

DECA: Deep viewpoint-Equivariant human pose estimation using Capsule Autoencoders

https://github.com/mohomran/neural_body_fitting

공식 코드

Neural Body Fitting: Unifying Deep Learning and Model-Based Human Pose and Shape Estimation

https://github.com/mookerr/varges

공식 코드

VarGes: Improving Variation in Co-Speech 3D Gesture Generation via StyleCLIPS

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