https://github.com/CXH-Research/ShadocNet
공식 코드ShaDocNet: Learning Spatial-Aware Tokens in Transformer for Document Shadow Removal
Papers with Code 아카이브
Shadow Detection
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 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/HarryHsing/Video-Instance-Shadow-Detection
공식 코드https://github.com/IVRL/Drone-Shadow-Tracking
공식 코드https://github.com/SorourMo/95-Cloud-An-Extension-to-38-Cloud-Dataset
공식 코드https://github.com/Yuki-11/NTIRE2023_ShadowRemoval_IIM_TTI
공식 코드NTIRE 2023 Image Shadow Removal Challenge Technical Report: Team IIM_TTI
https://github.com/aL3x-O-o-Hung/ultrasound-conidence-map-with-directed-graphs
공식 코드https://github.com/acecreamu/angularGAN
공식 코드Conditional GANs for Multi-Illuminant Color Constancy: Revolution or Yet Another Approach?
https://github.com/bcmi/object-shadow-generation-dataset-desobav2
공식 코드DESOBAv2: Towards Large-scale Real-world Dataset for Shadow Generation
https://github.com/cralence/silt
공식 코드SILT: Shadow-aware Iterative Label Tuning for Learning to Detect Shadows from Noisy Labels
https://github.com/eraserNut/ViSha
공식 코드https://github.com/esa/snerf
공식 코드Shadow Neural Radiance Fields for Multi-view Satellite Photogrammetry
https://github.com/facebookresearch/deepmask
공식 코드https://github.com/guanhuankang/shadowdetection2021
공식 코드https://github.com/haipengzhou856/tbgdiff
공식 코드Timeline and Boundary Guided Diffusion Network for Video Shadow Detection
https://github.com/harrytea/SwinShadow
공식 코드SwinShadow: Shifted Window for Ambiguous Adjacent Shadow Detection
https://github.com/harrytea/detect-anyshadow
공식 코드Detect Any Shadow: Segment Anything for Video Shadow Detection
https://github.com/leipingjie/adaptershadow
공식 코드AdapterShadow: Adapting Segment Anything Model for Shadow Detection
https://github.com/leipingjie/sam2video
공식 코드https://github.com/leipingjie/samshadow
공식 코드https://github.com/n-kubiak/rendetnet
공식 코드RenDetNet: Weakly-supervised Shadow Detection with Shadow Caster Verification
https://github.com/naoto0804/SynShadow
공식 코드Learning from Synthetic Shadows for Shadow Detection and Removal
https://github.com/nifangbaage/explicit-visual-prompt
공식 코드Explicit Visual Prompting for Low-Level Structure Segmentations
https://github.com/rmcong/sddnet_acmmm23
공식 코드SDDNet: Style-guided Dual-layer Disentanglement Network for Shadow Detection
https://github.com/stevewongv/InstanceShadowDetection
공식 코드https://github.com/stevewongv/SSIS
공식 코드https://github.com/whq-xxh/rvsd
공식 코드https://github.com/xw-hu/FSDNet
공식 코드Revisiting Shadow Detection: A New Benchmark Dataset for Complex World
https://github.com/xw-hu/unveiling-deep-shadows
공식 코드https://github.com/yihong-97/stict
공식 코드Video Shadow Detection via Spatio-Temporal Interpolation Consistency Training
https://github.com/zhangbaijin/sam-helps-shadow
공식 코드SAM-helps-Shadow:When Segment Anything Model meet shadow removal
https://github.com/zhangbaijin/spa-former-shadow-removal
공식 코드SpA-Former: Transformer image shadow detection and removal via spatial attention
https://github.com/zhangbaijin/spatial-transformer-shadow-removal
공식 코드SpA-Former: Transformer image shadow detection and removal via spatial attention
https://github.com/BalajSaleem/InstanceShadowDetection
https://github.com/IsHYuhi/ST-CGAN_Stacked_Conditional_Generative_Adversarial_Networks
https://github.com/Param-Raval/ipro
https://github.com/Param-Raval/shadow-sight
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.