Papers with Code 아카이브
Human Parsing
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 1
- 평가표
- 2
- 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/SonginCV/MAF_HDA
https://github.com/StephenEkaputra/Mask_RCNN-TinyPascalVOC
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/Wizaron/instance-segmentation-pytorch
Semantic Instance Segmentation with a Discriminative Loss Function
https://github.com/ZQPei/deep_sort_pytorch
https://github.com/ZhaoJ9014/Multi-Human-Parsing
https://github.com/ZhaoJ9014/Multi-Human-Parsing_MHP
https://github.com/alexalm4190/Mask_RCNN-Vizzy_Hand
https://github.com/alexander-pv/maskrcnn_tf2
https://github.com/alicranck/instance-seg
Semantic Instance Segmentation with a Discriminative Loss Function
https://github.com/alililia/ascend_maskrcnn_mobilenetv1
https://github.com/alililia/gpu_maskrcnn_mobilenetv1
https://github.com/andrewjong/SwapNet
Look into Person: Joint Body Parsing & Pose Estimation Network and A New Benchmark
https://github.com/asyrovprog/cs230project
https://github.com/ayoolaolafenwa/PixelLib
https://github.com/baodi23/hourglass-facekeypoints-detection
https://github.com/beassssry/U
https://github.com/bethgelab/siamese-mask-rcnn
https://github.com/boom85423/Cartoon-style-Stickers-Generator
https://github.com/bowu1004/instance_segmentation_RealSense
https://github.com/busyboxs/What-I-have-star
https://github.com/busyboxs/faster_rcnn_voc
https://github.com/casiopa/Madrid_Rooftops
https://github.com/chaneyddtt/UDA-Animal-Pose
https://github.com/charlesYangM/py-faster-rcnn-80.28
https://github.com/charlesshang/fastmaskrcnn
https://github.com/chenwuperth/ClaRAN
https://github.com/chihyanghsu0805/object_detection_yolo
https://github.com/chuanqichen/deepcoaching
https://github.com/code-implementation1/Code9/tree/main/MaskRCNN/maskrcnn_mobilenetv1
https://github.com/cokowpublic/Nuclei-Segmentation
https://github.com/collectionslab/Omniscribe
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.