https://github.com/ShaoweiSong0718/HigherHRNet-Human-Pose-Estimation
HigherHRNet: Scale-Aware Representation Learning for Bottom-Up Human Pose Estimation
Papers with Code 아카이브
3D Human Pose Estimation
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- 평가표
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- 보존된 평가 기록
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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/ShirleyMaxx/ContextPose-PyTorch-release
Context Modeling in 3D Human Pose Estimation: A Unified Perspective
https://github.com/Shritesh99/100DaysofMLCodeChallenge
https://github.com/Shritesh99/Image_Super_Resolution
https://github.com/SimoneDutto/EDSR
https://github.com/StupidmanTan/facebookresearch
https://github.com/SyBorg91/pose-estimation-detection
Lifting from the Deep: Convolutional 3D Pose Estimation from a Single Image
https://github.com/SyedUmaidAhmed/Pose-Detection-Sitting-Standing
Lifting from the Deep: Convolutional 3D Pose Estimation from a Single Image
https://github.com/TaatiTeam/stgcn_parkinsonism_prediction
Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
https://github.com/TahmasbiM/Example
https://github.com/TanakitInt/SRCNN-anime
https://github.com/ThibaultGROUEIX/3D-CODED
https://github.com/TomokiKomiya/SRGAN-keras
https://github.com/Tudouu/stgcn_light_op
Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
https://github.com/UBC-Computer-Vision-Group/DwNet
https://github.com/VNOpenAI/tf-blazepose
https://github.com/Varun-Tandon14/Implementation-of-Cross-View-Tracking-for-Multi-Human-3D-Pose-Estimation-at-over-100-FPS
Cross-View Tracking for Multi-Human 3D Pose Estimation at over 100 FPS
https://github.com/Vill-Lab/2022-TIP-HCGA
Deep High-Resolution Representation Learning for Human Pose Estimation
https://github.com/WarrenGreen/srcnn
https://github.com/Watson-BCA/HumanPostureRecognition
Lifting from the Deep: Convolutional 3D Pose Estimation from a Single Image
https://github.com/Weifeng73/Zero-Shot-Super-resolution
https://github.com/XPixelGroup/BasicSR
BasicVSR: The Search for Essential Components in Video Super-Resolution and Beyond
https://github.com/XinArkh/VNect
VNect: Real-time 3D Human Pose Estimation with a Single RGB Camera
https://github.com/XinzeWu/st-GCN
Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
https://github.com/XiuyuLiu/Application-of-Deep-Learning-models-in-Single-Image-Super-Resolution
https://github.com/YangChangHee/ICCV2023_SEFD_RELEASE
https://github.com/YangYangTaoTao/V2V-PoseNet_Pytorch
https://github.com/YanyingZH/srgan-esrgan-pytorch
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/YapengTian/TDAN-VSR-CVPR-2020
TDAN: Temporally Deformable Alignment Network for Video Super-Resolution
https://github.com/YapengTian/TDAN_VSR
TDAN: Temporally Deformable Alignment Network for Video Super-Resolution
https://github.com/YeongHyeon/Super-Resolution_CNN
https://github.com/YeongHyeon/Super-Resolution_CNN-PyTorch
https://github.com/Yongjjun/singleshotpose
https://github.com/Yuki0114/UndergraduateThesis_SRCNN_keras
https://github.com/YvanG/VQGAN-CLIP
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/ZHONGCHUYUN/3d_pose_baseline_tf
A simple yet effective baseline for 3d human pose estimation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.