Papers with Code 아카이브
3D Human Pose Estimation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 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/CompVis/unsupervised-part-segmentation
Unsupervised Part-Based Disentangling of Object Shape and Appearance
https://github.com/CorentinMAG/SRGAN
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/D1vyansh/BodyJointDetection
https://github.com/Daniil-Osokin/gccpm-look-into-person-cvpr19.pytorch
https://github.com/Daniil-Osokin/lightweight-human-pose-estimation-3d-demo.pytorch
Single-Shot Multi-Person 3D Pose Estimation From Monocular RGB
https://github.com/Darius-Liesis/HRNet-works
HigherHRNet: Scale-Aware Representation Learning for Bottom-Up Human Pose Estimation
https://github.com/DenisTome/Lifting-from-the-Deep-release
Lifting from the Deep: Convolutional 3D Pose Estimation from a Single Image
https://github.com/Dictator890/ESRGAN-Android-Demo
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/DixinFan/st-gcn
Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
https://github.com/DreamTechAI/Direct3D
Direct3D: Scalable Image-to-3D Generation via 3D Latent Diffusion Transformer
https://github.com/DreamTechAI/Direct3D-S2
Direct3D-S2: Gigascale 3D Generation Made Easy with Spatial Sparse Attention
https://github.com/Droliven/pymaf_reimplementation
PyMAF: 3D Human Pose and Shape Regression with Pyramidal Mesh Alignment Feedback Loop
https://github.com/DwightFoster/Pytorch-TecoGan
Learning Temporal Coherence via Self-Supervision for GAN-based Video Generation
https://github.com/ECE740F21T01/pytorch-pose-hg-3d
Towards 3D Human Pose Estimation in the Wild: a Weakly-supervised Approach
https://github.com/Feynman1999/MgeEditing
Video Super-Resolution with Recurrent Structure-Detail Network
https://github.com/Feynman1999/basicVSR_mge
BasicVSR: The Search for Essential Components in Video Super-Resolution and Beyond
https://github.com/Fickle519/stockforecastingmodelbasedon_XGboost
https://github.com/FirstPotatoMan/TensorflowJS_ESRGAN
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/Fivefold/SRCNN
https://github.com/Fuhui-Chen/TecoGAN
Learning Temporal Coherence via Self-Supervision for GAN-based Video Generation
https://github.com/GeyuanZhang/st-gcn-master
Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
https://github.com/GilbertoQ/Bioinformatics
https://github.com/GitHubXlong/TecoGAN
Learning Temporal Coherence via Self-Supervision for GAN-based Video Generation
https://github.com/GloryyrolG/MHEntropy
https://github.com/Gowti-AiboT/GAN-based-SISR-Keras
https://github.com/GuillaumeDufau/Image-super-resolution-vdsr
Accurate Image Super-Resolution Using Very Deep Convolutional Networks
https://github.com/HERMINDERSINGH1234/ML_Extra_Resolution_Increases
Learning Temporal Coherence via Self-Supervision for GAN-based Video Generation
https://github.com/HRNet/HRNet-Facial-Landmark-Detection
Deep High-Resolution Representation Learning for Human Pose Estimation
https://github.com/HRNet/HRNet-Human-Pose-Estimation
Deep High-Resolution Representation Learning for Human Pose Estimation
https://github.com/HRNet/HRNet-Image-Classification
Deep High-Resolution Representation Learning for Human Pose Estimation
https://github.com/HRNet/HRNet-MaskRCNN-Benchmark
Deep High-Resolution Representation Learning for Human Pose Estimation
https://github.com/HRNet/HRNet-Object-Detection
Deep High-Resolution Representation Learning for Human Pose Estimation
https://github.com/HRNet/HRNet-Semantic-Segmentation
Deep High-Resolution Representation Learning for Human Pose Estimation
https://github.com/Harrypotterrrr/EDVR
EDVR: Video Restoration with Enhanced Deformable Convolutional Networks
https://github.com/Hem7513/Decision-Trees-and-XGBoost-Algorithm-Documentation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.