https://github.com/cmbagents/cmbagent
AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation
Papers with Code 아카이브
3D Human Pose Estimation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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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/code-implementation1/Code3/tree/main/ESRGAN
Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data
https://github.com/code-implementation1/Code6/tree/main/ras
Recurrent Back-Projection Network for Video Super-Resolution
https://github.com/code-implementation1/Code7/tree/main/RefineNet
RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation
https://github.com/code-implementation1/Code9/tree/main/EDSR
BasicVSR: The Search for Essential Components in Video Super-Resolution and Beyond
https://github.com/code-implementation1/Code9/tree/main/hrnet
HigherHRNet: Scale-Aware Representation Learning for Bottom-Up Human Pose Estimation
https://github.com/coulsonlee/dy-dca-eccv2024
Towards High-Quality and Efficient Video Super-Resolution via Spatial-Temporal Data Overfitting
https://github.com/cscss/DBVSR
https://github.com/cviaai/PSF-GAN-ESTIMATION
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/cvlab-epfl/single-stage-pose
https://github.com/d-shivam/Pose-estimation-based-action-recognition-for-help-Situation-Identification
Deep High-Resolution Representation Learning for Human Pose Estimation
https://github.com/dajes/DensePose-TorchScript
https://github.com/dalexanderch/CFD
https://github.com/darkAlert/vibe-rt
VIBE: Video Inference for Human Body Pose and Shape Estimation
https://github.com/dcvl-3d/instancehmr_release
https://github.com/deepak112/Keras-SRGAN
https://github.com/deepmodeling/Uni-Mol
Uni-Mol Docking V2: Towards Realistic and Accurate Binding Pose Prediction
https://github.com/delirecs/facial-keypoints-heatmaps
https://github.com/denilson020898/baseline_3d_pose
A simple yet effective baseline for 3d human pose estimation
https://github.com/digital-thinking/deep-posemachine
https://github.com/dizhongzhu/Humanbody_Literatures
Keep it SMPL: Automatic Estimation of 3D Human Pose and Shape from a Single Image
https://github.com/djsinghnegi/SRINImageEnhancemrntGAN
https://github.com/doantienthongbku/ESRGAN
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/dokyeongK/Pytorch_SRCNN
https://github.com/dokyeongK/Single-Image-Super-Resolution-Reimplemenation
https://github.com/dragonbook/V2V-PoseNet-pytorch
https://github.com/drhdr-user/drhdr
EDVR: Video Restoration with Enhanced Deformable Convolutional Networks
https://github.com/dronefreak/human-action-classification
Lifting from the Deep: Convolutional 3D Pose Estimation from a Single Image
https://github.com/ducongju/HRNet
Deep High-Resolution Representation Learning for Human Pose Estimation
https://github.com/eliasboughosn/Spatial-Temporal-Graph-Convolutional-Networks
Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
https://github.com/ericksiavichay/cs230-final-project
Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
https://github.com/eriklindernoren/PyTorch-GAN
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/facebookresearch/DensePose
https://github.com/facebookresearch/detectron
https://github.com/facebookresearch/detectron2/tree/master/projects/DensePose/
https://github.com/facebookresearch/multiface
MeshTalk: 3D Face Animation from Speech using Cross-Modality Disentanglement
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.