Papers with Code 아카이브
3D Interacting Hand Pose Estimation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/joykour/COCO-Dataset-2018-Stuff-Segmentation-Challenge
https://github.com/jxr326/swinmcnet
RGB-T Image Saliency Detection via Collaborative Graph Learning
https://github.com/kazuto1011/deeplab-pytorch
https://github.com/mathilde-b/SRDA
A Curriculum Domain Adaptation Approach to the Semantic Segmentation of Urban Scenes
https://github.com/mohsenkheirandishfard/IS4
https://github.com/nightrome/cocostuff10k
https://github.com/open-mmlab/mmpose
https://github.com/perrying/ssn-pytorch
https://github.com/pixar0407/depth_map
https://github.com/semiquark1/boruvka-superpixel
https://github.com/tntek/dspnet
Self-Supervision with Superpixels: Training Few-shot Medical Image Segmentation without Annotation
https://github.com/valeoai/bravo_challenge
https://github.com/vinceecws/SegNet_PyTorch
https://github.com/vsomnath/holoprot
https://github.com/waggle-sensor/plugin-water-detector
https://github.com/woonhahaha/place-classification
https://github.com/yhlleo/DeepSegmentor
https://github.com/yuxi120407/transfer_learning
Collaborative Annotation of Semantic Objects in Images with Multi-granularity Supervisions
https://github.com/zjlab-ammi/q-net
Self-Supervision with Superpixels: Training Few-shot Medical Image Segmentation without Annotation
https://github.com/zllrunning/deeplab-pytorch-crf
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.