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/lixiaolei1982/DenseNet-base-Mask-RCNN-for-Human-Pose-Estimation

Mask R-CNN

https://github.com/longcw/roialign.pytorch

Mask R-CNN

https://github.com/louisyuzhe/car-damage-detector

Mask R-CNN

https://github.com/ls5122/mask-rcnn

Mask R-CNN

https://github.com/lucylow/salty-wet-man

Mask R-CNN

https://github.com/lukoucky/image_recommendation

Mask R-CNN

https://github.com/maxfrei750/DeepParticleNet

Mask R-CNN

https://github.com/maxfrei750/FibeR-CNN

Mask R-CNN

https://github.com/miaohua1982/simple_fasterrcnn_pytorch

Mask R-CNN

https://github.com/mic-dkfz/medicaldetectiontoolkit

Mask R-CNN

https://github.com/mindspore-ai/models/tree/master/official/cv/maskrcnn

Mask R-CNN

https://github.com/mindspore-courses/External-Attention-MindSpore/blob/main/model/attention/CrissCrossAttention.py

CCNet: Criss-Cross Attention for Semantic Segmentation

https://github.com/mirzaevinom/data_science_bowl_2018

Mask R-CNN

https://github.com/modelscope/modelscope

Beyond Appearance: a Semantic Controllable Self-Supervised Learning Framework for Human-Centric Visual Tasks

https://github.com/mstfakts/building-detection-maskrcnn

Mask R-CNN

https://github.com/multimodallearning/pytorch-mask-rcnn

Mask R-CNN

https://github.com/muyistarsky/MaskRCNN

Mask R-CNN

https://github.com/nikhithakarennagari/1311

Mask R-CNN

https://github.com/nikhithakarennagari/Git

Mask R-CNN

https://github.com/noelcodes/Mask_RCNN

Mask R-CNN

https://github.com/nyoki-mtl/pytorch-discriminative-loss

Semantic Instance Segmentation with a Discriminative Loss Function

https://github.com/o-evgeny/MRCNN_DeepFashion2

Mask R-CNN

https://github.com/open-edge-platform/geti

Mask R-CNN

https://github.com/open-edge-platform/training_extensions

Mask R-CNN

https://github.com/open-mmlab/mmpose

Understanding Humans in Crowded Scenes: Deep Nested Adversarial Learning and A New Benchmark for Multi-Human Parsing

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.