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/Mind23-2/MindCode-3/tree/main/HMR
https://github.com/Mind23-2/MindCode-5/tree/main/rbpn
Recurrent Back-Projection Network for Video Super-Resolution
https://github.com/MindSpore-paper-code-2/code2/tree/main/rbpn
Recurrent Back-Projection Network for Video Super-Resolution
https://github.com/MindSpore-paper-code-3/code4/tree/main/HMR
https://github.com/MindSpore-paper-code-3/code5/tree/main/RefineNet
RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation
https://github.com/MindSpore-scientific-2/code-10/tree/main/pixelshuffle1d
https://github.com/MindSpore-scientific-2/code-8/tree/main/pixelshuffle1d
https://github.com/MindSpore-scientific/code-1/tree/main/pixelshuffle1d
https://github.com/MindSpore-scientific/code-10/tree/main/pixelshuffle1d
https://github.com/MindSpore-scientific/code-4/tree/main/pixelshuffle1d
https://github.com/ModelBunker/Lightweight-OpenPose-PyTorch
Single-Shot Multi-Person 3D Pose Estimation From Monocular RGB
https://github.com/MohamedAliRashad/Crystal
EDVR: Video Restoration with Enhanced Deformable Convolutional Networks
https://github.com/Mohitkr95/Image-Super-Resolution
https://github.com/MrCat9/Sklearn_Note
https://github.com/NU-LL/lighttrack-
Deep High-Resolution Representation Learning for Human Pose Estimation
https://github.com/NVIDIA/UnsupervisedLandmarkLearning
Unsupervised Part-Based Disentangling of Object Shape and Appearance
https://github.com/NVlabs/PAMTRI
Deep High-Resolution Representation Learning for Human Pose Estimation
https://github.com/Ne-ki-tos/Super_res
https://github.com/Neilblaze/Aerowave
https://github.com/Nhat-Thanh/ESPCN-Pytorch
https://github.com/Nhat-Thanh/ESPCN-TF
https://github.com/Nhat-Thanh/SRCNN-Pytorch
https://github.com/Nhat-Thanh/SRCNN-TF
https://github.com/Nhat-Thanh/VDSR-Pytorch
Accurate Image Super-Resolution Using Very Deep Convolutional Networks
https://github.com/Oishani/Machine-Learning-Projects
https://github.com/One-sixth/pixelshuffle_invert_pytorch
https://github.com/PaddlePaddle/PaddleDetection
Deep High-Resolution Representation Learning for Human Pose Estimation
https://github.com/PaddlePaddle/PaddleVideo/blob/develop/docs/zh-CN/model_zoo/recognition/stgcn.md
Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
https://github.com/Pea-Shooter/ADNet
EDVR: Video Restoration with Enhanced Deformable Convolutional Networks
https://github.com/Powercoder64/TAA-GCN
Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
https://github.com/Pulkitdzrt/ML-Image-Super-Resolution
https://github.com/RezisEwig/esrgan
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/SJHNJU/VDSR
Accurate Image Super-Resolution Using Very Deep Convolutional Networks
https://github.com/SJTU-DL-lab/3d-pose-baseline
A simple yet effective baseline for 3d human pose estimation
https://github.com/SeonghwanSeo/RxnFlow
PharmacoNet: Accelerating Large-Scale Virtual Screening by Deep Pharmacophore Modeling
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.