Papers with Code 아카이브
Human Parsing
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 1
- 평가표
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- 보존된 평가 기록
- 7
Human parsing is the task of segmenting a human image into different fine-grained semantic parts such as head, torso, arms and legs.
<span style="color:grey; opacity: 0.6">( Image credit: Multi-Human-Parsing (MHP) )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/paradisetechsoftsolutions/Deep-learning-model-using-Mask-R-CNN-for-predicting-AC-remote
https://github.com/phtruongan/py-faster-rcnn-docker
https://github.com/phykn/film-defect-detection
https://github.com/pj1920/mask-r-cnn
https://github.com/polospeter/TensorFlow-Advanced-Techniques-Specialization
https://github.com/pvdhove/owl-mask-rcnn
https://github.com/qilei123/pyfasterrcnn
https://github.com/qq330488563/TEST
https://github.com/quocdat32461997/Mask_RCNN
https://github.com/ravenwritingdesk/py-faster-rcnn-master
https://github.com/raymon-tian/hourglass-facekeypoints-detection
https://github.com/rh01/fast-rnn
https://github.com/rh01/faster-rcnn
https://github.com/rickyHong/py-faster-rcnn-repl
https://github.com/rickyHong/py-faster-rcnn-repl-cudnn5-support
https://github.com/saehan-choi/pixellib_auto_labelling
https://github.com/samsh19/ML_project
https://github.com/sbetageri/MaskRCNN
https://github.com/scolocke/Traffic_Sign_ID_GTSRB_GTSDB
https://github.com/soulguy/Faster-rcnn
https://github.com/ssanyachetwani/Fashion-Trend-Detection-and-Recommendation-Model
https://github.com/stanleycelestin1/AirsimDetectron
https://github.com/sunhui1234/haha
https://github.com/sunqiangxtcsun/faster-rcnn
https://github.com/tensorflow/models/tree/master/official/vision
https://github.com/tensorpack/tensorpack/tree/master/examples/FasterRCNN
https://github.com/toytiny/radarocc
milliFlow: Scene Flow Estimation on mmWave Radar Point Cloud for Human Motion Sensing
https://github.com/trackinglaboratory/tracklab
Body Part-Based Representation Learning for Occluded Person Re-Identification
https://github.com/tryolabs/luminoth
https://github.com/vimalabs/VIMA
https://github.com/vlsomers/keypoint_promptable_reidentification
Body Part-Based Representation Learning for Occluded Person Re-Identification
https://github.com/waspinator/deep-learning-explorer
https://github.com/xiuyu0000/papers_with_examples/tree/main/maskrcnn
https://github.com/xjnpark/ds
https://github.com/xunhen/py-faster-rcnn-wjc
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.