Keypoint Detection
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Keypoint Detection is essential for analyzing and interpreting images in computer vision. It involves simultaneously detecting and localizing interesting points in an image. Keypoints, also known as interest points, are spatial locations or points in the image that define what is interesting or what stands out. They are invariant to image rotation, shrinkage, translation, distortion, etc. Keypoints examples are body joints, facial landmarks, or any other salient points in objects. Keypoints have uses in problems such as pose estimation, object detection and tracking, facial analysis, and augmented reality.
<span style="color:grey; opacity: 0.6">( Image credit: PifPaf: Composite Fields for Human Pose Estimation; "Learning to surf" by fotologic, license: CC-BY-2.0 )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/jianing-sun/Mask-YOLO
https://github.com/jingpeilu/keypoint_optimization
Pose Estimation for Robot Manipulators via Keypoint Optimization and Sim-to-Real Transfer
https://github.com/jklife3/maskrcnn-impl
https://github.com/jodumagpi/Xray-ObjSep-v1
https://github.com/jooyounghun/AI-Team-5
https://github.com/jordiae/DeepLearning-MAI
https://github.com/jp-sm/jp-sm.github.io
https://github.com/jpviguerasguillen/feedback-non-local-attention-fnla
https://github.com/jpviguerasguillen/feedback-non-local-attention_fNLA
https://github.com/jreisam/Unity-OpenPose-Edutable
Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
https://github.com/jremillard/images-to-osm
https://github.com/jyhengcoder/Triplet-Attention-tf
https://github.com/jylins/core-text
https://github.com/k-miran/hear
Deep High-Resolution Representation Learning for Human Pose Estimation
https://github.com/kaijieshi7/Dynamic-convolution-Pytorch
https://github.com/kbardool/mrcnn3
https://github.com/kdethoor/panoptictorch
https://github.com/ken724049/action-recognition
Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
https://github.com/kohillyang/mx-detection
OpenPose: Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
https://github.com/krantirk/py-faster-rcnn
https://github.com/krishnac7/OpenPose
Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
https://github.com/krutikabapat/Deep-Learning-based-OpenPose-Estimation
Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
https://github.com/landskape-ai/triplet-attention
https://github.com/laobaiswag/openpose1
Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
https://github.com/laowang666888/ECSP1
CrowdPose: Efficient Crowded Scenes Pose Estimation and A New Benchmark
https://github.com/laowang666888/HRNET
Deep High-Resolution Representation Learning for Human Pose Estimation
https://github.com/lcxzzz0113/CenterNet
https://github.com/lee-man/movenet
https://github.com/leeyegy/SimDR
https://github.com/leeyegy/simcc
https://github.com/leobean/CenterNet_oriented
https://github.com/leochangzliao/OPBM
https://github.com/leonardhan1979/fasterRCNN
https://github.com/liang-faan/openpose
Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
https://github.com/lichengunc/mask-faster-rcnn
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.