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/Pxtri2156/AdelaiDet_v2
https://github.com/Qinhj07/ATOMCode
https://github.com/RACHANAMOVVA09/CenterNet
https://github.com/RaiyaniNirav/Mask-R-CNN-for-water-detection
https://github.com/RajArPatra/Super-OCR
https://github.com/Rakeshvd/Instance-Segmenation-of-MRI-scan-using-Mask-RCNN
https://github.com/Rakeshvd/Semantic-Segmenation-of-MRI-scan-using-Mask-RCNN
https://github.com/RituYadav92/Radar-RGB-Attentive-Multimodal-Object-Detection
https://github.com/RoyaSabbagh/mobile_manipulation_planning
OpenPose: Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
https://github.com/SAtacker/PosenetTflite
https://github.com/SUYEgit/Surgery-Robot-Detection-Segmentation
https://github.com/Saadbutt321/Conversion-of-Pakistan-Sign-Language-into-Text-and-Speech-using-OpenPose-and-Machine-Learning
Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
https://github.com/SfTI-Robotics/ROS-label-node
https://github.com/Shiaoming/ALIKED
ALIKE: Accurate and Lightweight Keypoint Detection and Descriptor Extraction
https://github.com/Sobeit-Tim/NuguEyeTest
Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
https://github.com/Somoina/OpenHorse
OpenPose: Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
https://github.com/SonginCV/GMPHD_MAF
https://github.com/SonginCV/GMPHD_SAF
https://github.com/SonginCV/MAF_HDA
https://github.com/Ssong24/CenterNet_Custom
https://github.com/StephenEkaputra/Mask_RCNN-TinyPascalVOC
https://github.com/Stick-To/CenterNet-tensorflow
https://github.com/SukhyunCho/NTU_motion_sim_annotations
MultiPoseNet: Fast Multi-Person Pose Estimation using Pose Residual Network
https://github.com/SunJuil-Ty/simplebaselines-mindspore
https://github.com/TArdelean/DynamicConvolution
https://github.com/TejasBajania/Mtech_pro
https://github.com/TejasBajania/Mtech_thesis_project
https://github.com/ThanhDinhDat/center_net_points
https://github.com/TuSimple/mx-maskrcnn
https://github.com/UPCLJ/py-faster-rcnn
https://github.com/Vill-Lab/2022-TIP-HCGA
Deep High-Resolution Representation Learning for Human Pose Estimation
https://github.com/WYGNG/CenterNet-Pro
https://github.com/WYGNG/USTC_SSE_Project
https://github.com/Wastoon/XinTong_CenterNet
https://github.com/WavesUR/embedded_TSM
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.