https://github.com/yijie0710/GeoNet_pytorch
GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera Pose
Papers with Code 아카이브
Pose Estimation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 17
- 평가표
- 31
- 보존된 평가 기록
- 235
Pose Estimation is a computer vision task where the goal is to detect the position and orientation of a person or an object. Usually, this is done by predicting the location of specific keypoints like hands, head, elbows, etc. in case of Human Pose Estimation.
A common benchmark for this task is MPII Human Pose
<span style="color:grey; opacity: 0.6">( Image credit: Real-time 2D Multi-Person Pose Estimation on CPU: Lightweight OpenPose )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/yikegami/openpose
https://github.com/yinzhiyan43/openpose-dev
https://github.com/yj-littlesky/py-faster-rcnn
https://github.com/yjn870/srcnn-pytorch
https://github.com/ykasten/layered-neural-atlases
https://github.com/yktangac/CenterHarDNet
https://github.com/ykzzyk/vision6d
Normalized Object Coordinate Space for Category-Level 6D Object Pose and Size Estimation
https://github.com/ylabbe/cosypose
CosyPose: Consistent multi-view multi-object 6D pose estimation
https://github.com/ylxiao88/CenterNet
https://github.com/yohanshin/WHAM
WHAM: Reconstructing World-grounded Humans with Accurate 3D Motion
https://github.com/yongheng1991/qec_net
https://github.com/yongsheng268/DensePose
https://github.com/yongsheng268/OpenPose
https://github.com/yshah43/DPOD
https://github.com/yslenjoy/machine_learning_SuperResolution
Accurate Image Super-Resolution Using Very Deep Convolutional Networks
https://github.com/ytongbai/SemanticPartDetection
Unsupervised learning of object semantic parts from internal states of CNNs by population encoding
https://github.com/yttrilab/b-soid
DeeperCut: A Deeper, Stronger, and Faster Multi-Person Pose Estimation Model
https://github.com/ytx21cn/CDCL-human-seg
Cross-Domain Complementary Learning Using Pose for Multi-Person Part Segmentation
https://github.com/yuansun-xjtu/icomma
iComMa: Inverting 3D Gaussian Splatting for Camera Pose Estimation via Comparing and Matching
https://github.com/yuanyuanfyy/yycode/tree/mindsporecode/AlphaPose
https://github.com/yuanyuanli85/Stacked_Hourglass_Network_Keras
https://github.com/yuanyuanli85/tf-hrnet
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/yubaoliu/rds-slam
https://github.com/yufu-wang/6d_pose
Semantic keypoint-based pose estimation from single RGB frames
https://github.com/yufu-wang/PromptHMR
https://github.com/yukichou/PET
Deep High-Resolution Representation Learning for Visual Recognition
https://github.com/yukitsuji/chainer_function
https://github.com/yuqizhu/covid19-classification
Cross-Domain Complementary Learning Using Pose for Multi-Person Part Segmentation
https://github.com/yusukey03012/deformer
https://github.com/yuxng/PoseCNN
PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes
https://github.com/yz-cnsdqz/PSI-release
https://github.com/zaverichintan/Intention-based-Long-Term-Human-Motion-Anticipation
https://github.com/zc-alexfan/arctic
Benchmarks and Challenges in Pose Estimation for Egocentric Hand Interactions with Objects
https://github.com/zccyman/pose_estimation/tree/master/lib/models/pose_pcr.py
https://github.com/zczcwh/potter
POTTER: Pooling Attention Transformer for Efficient Human Mesh Recovery
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.