Papers with Code 아카이브

Object Segmentation

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

3

평가표

1

보존된 평가 기록

2

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/thograce/bgnet

Context-aware Cross-level Fusion Network for Camouflaged Object Detection

https://github.com/tryolabs/luminoth

Mask R-CNN

https://github.com/tuvovan/Unet-with-EfficientnetB7-Backbone

UNet++: A Nested U-Net Architecture for Medical Image Segmentation

https://github.com/vimalabs/VIMA

Mask R-CNN

https://github.com/waspinator/deep-learning-explorer

Mask R-CNN

https://github.com/xiuyu0000/papers_with_examples/tree/main/maskrcnn

Mask R-CNN

https://github.com/xjnpark/ds

Mask R-CNN

https://github.com/xuebinqin/BASNet

Boundary-Aware Segmentation Network for Mobile and Web Applications

https://github.com/xueliancheng/slt-net

Implicit Motion Handling for Video Camouflaged Object Detection

https://github.com/xunhen/py-faster-rcnn-wjc

Mask R-CNN

https://github.com/xzabg/faster-rcnn-with-Caltech

Mask R-CNN

https://github.com/yangyucheng000/Egnet

https://github.com/yangyucheng000/MSpaper/tree/main/UNet3%2B

UNet++: A Nested U-Net Architecture for Medical Image Segmentation

https://github.com/yangyucheng000/Mask-RCNN

Mask R-CNN

https://github.com/yangyucheng000/maskrcnn_mobilenetv1

Mask R-CNN

https://github.com/yczhang1017/SSD_resnet_pytorch

Mask R-CNN

https://github.com/yingkaisha/keras-unet-collection

UNet++: A Nested U-Net Architecture for Medical Image Segmentation

https://github.com/yj-littlesky/py-faster-rcnn

Mask R-CNN

https://github.com/ykasten/layered-neural-atlases

Mask R-CNN

https://github.com/yubaoliu/rds-slam

Mask R-CNN

https://github.com/yuwenlo/hardnet-dfus

PraNet: Parallel Reverse Attention Network for Polyp Segmentation

https://github.com/zhangchi9/Airbus_Ship_Detection

Mask R-CNN

https://github.com/zhong110020/py-faster-rcnn

Mask R-CNN

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