Papers with Code 아카이브

Shadow Detection

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

1

평가표

2

보존된 평가 기록

32

코드

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

https://github.com/dfrisinghelli/pysegcnn

Cloud and Cloud Shadow Segmentation for Remote Sensing Imagery via Filtered Jaccard Loss Function and Parametric Augmentation

https://github.com/dveyarangi/cloud-net-plus

Cloud and Cloud Shadow Segmentation for Remote Sensing Imagery via Filtered Jaccard Loss Function and Parametric Augmentation

https://github.com/eraserNut/MTMT

https://github.com/gmlee329/InstanceShadowDetection

Instance Shadow Detection

https://github.com/jiaruixu/st-cgan

Stacked Conditional Generative Adversarial Networks for Jointly Learning Shadow Detection and Shadow Removal

https://github.com/kjybinp/SCGAN

Stacked Conditional Generative Adversarial Networks for Jointly Learning Shadow Detection and Shadow Removal

https://github.com/lmhieu612/adnet_demo

A+D Net: Training a Shadow Detector with Adversarial Shadow Attenuation

https://github.com/nifangbaage/explict-visual-prompt

Explicit Visual Prompting for Universal Foreground Segmentations

https://github.com/sepidehhosseinzadeh/Fast-Shadow-Detection

Fast Shadow Detection from a Single Image Using a Patched Convolutional Neural Network

https://github.com/stevewongv/dsc-pytorch

Direction-aware Spatial Context Features for Shadow Detection

https://github.com/tianrun-chen/sam-adapter-pytorch

SAM Fails to Segment Anything? -- SAM-Adapter: Adapting SAM in Underperformed Scenes: Camouflage, Shadow, Medical Image Segmentation, and More

https://github.com/xw-hu/CUHK-Shadow

Revisiting Shadow Detection: A New Benchmark Dataset for Complex World

https://github.com/xw-hu/DSC

Direction-aware Spatial Context Features for Shadow Detection

https://github.com/zijundeng/BDRAR

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