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/lincaiming/py-faster-rcnn-update
https://github.com/lincaiming/py-faster-rcnn-windows
https://github.com/lixiaolei1982/DenseNet-base-Mask-RCNN-for-Human-Pose-Estimation
https://github.com/lncarter/Openpose
Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
https://github.com/longcw/roialign.pytorch
https://github.com/louisyuzhe/car-damage-detector
https://github.com/ls5122/mask-rcnn
https://github.com/lucylow/salty-wet-man
https://github.com/lukoucky/image_recommendation
https://github.com/lwxGitHub123/openpose
Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
https://github.com/lwxGitHub123/openpose20200610
Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
https://github.com/lyqcom/alphapose
https://github.com/maudzung/CenterNet3D-PyTorch
https://github.com/maudzung/RTM3D
https://github.com/maudzung/SFA3D
https://github.com/maudzung/super-fast-accurate-3d-object-detection
https://github.com/maxfrei750/DeepParticleNet
https://github.com/maxfrei750/FibeR-CNN
https://github.com/melgor/pyface
UMDFaces: An Annotated Face Dataset for Training Deep Networks
https://github.com/mgolnezhad/openpose
Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
https://github.com/mhw32/contrastive-ring-public
Conditional Negative Sampling for Contrastive Learning of Visual Representations
https://github.com/miaohua1982/simple_fasterrcnn_pytorch
https://github.com/mic-dkfz/medicaldetectiontoolkit
https://github.com/michel-liu/grouppose
Explicit Box Detection Unifies End-to-End Multi-Person Pose Estimation
https://github.com/michel-liu/grouppose-paddle
Explicit Box Detection Unifies End-to-End Multi-Person Pose Estimation
https://github.com/mindspore-ai/models/blob/master/research/cv/simple_baselines/
https://github.com/mindspore-ai/models/tree/master/official/cv/maskrcnn
https://github.com/mindspore-ai/models/tree/master/official/cv/openpose
Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
https://github.com/mindspore-ai/models/tree/master/official/cv/simple_pose
https://github.com/mindspore-ai/models/tree/master/research/cv/AlphaPose
https://github.com/mindspore-ai/models/tree/master/research/cv/ArtTrack
https://github.com/mindspore-ai/models/tree/master/research/cv/centernet_resnet50_v1
https://github.com/mindspore-ai/models/tree/master/research/cv/fairmot
https://github.com/mindspore-courses/External-Attention-MindSpore/blob/main/model/attention/PolarizedSelfAttention.py
Polarized Self-Attention: Towards High-quality Pixel-wise Regression
https://github.com/mindspore-courses/External-Attention-MindSpore/blob/main/model/attention/TripletAttention.py
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.