Papers with Code 아카이브
Multi-Person Pose Estimation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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Multi-person pose estimation is the task of estimating the pose of multiple people in one frame.
<span style="color:grey; opacity: 0.6">( Image credit: Human Pose Estimation with TensorFlow )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
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/Rocketbase-AI/rockets-lightpose
Real-time 2D Multi-Person Pose Estimation on CPU: Lightweight OpenPose
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/ShaoweiSong0718/HigherHRNet-Human-Pose-Estimation
HigherHRNet: Scale-Aware Representation Learning for Bottom-Up Human Pose Estimation
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/StephenEkaputra/Mask_RCNN-TinyPascalVOC
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/TeCSAR-UNCC/EfficientHRNet
EfficientHRNet: Efficient Scaling for Lightweight High-Resolution Multi-Person Pose Estimation
https://github.com/TejasBajania/Mtech_pro
https://github.com/TejasBajania/Mtech_thesis_project
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/Xingyu-Romantic/RMPose_PAF
Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
https://github.com/ZJX9999/art_track
https://github.com/ZQPei/deep_sort_pytorch
https://github.com/Zero-nnkn/ml-utils/blob/main/cv/pose/openpose_predictor.py
OpenPose: Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
https://github.com/abhi1kumar/hrnet_pose_single_gpu
Deep High-Resolution Representation Learning for Human Pose Estimation
https://github.com/aim-uofa/AdelaiDet
https://github.com/aim-uofa/adet
https://github.com/alexalm4190/Mask_RCNN-Vizzy_Hand
https://github.com/alexander-pv/maskrcnn_tf2
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.