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Image Shadow Removal
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논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Controlling the Latent Diffusion Model for Generative Image Shadow Removal via Residual Generation
ShadowMamba: State-Space Model with Boundary-Region Selective Scan for Shadow Removal
OmniSR: Shadow Removal under Direct and Indirect Lighting
SoftShadow: Leveraging Penumbra-Aware Soft Masks for Shadow Removal
Soft-Hard Attention U-Net Model and Benchmark Dataset for Multiscale Image Shadow Removal
Single-Image Shadow Removal Using Deep Learning: A Comprehensive Survey
ShadowRefiner: Towards Mask-free Shadow Removal via Fast Fourier Transformer
Benchmarking Adversarial Robustness of Image Shadow Removal with Shadow-adaptive Attacks
NTIRE 2023 Image Shadow Removal Challenge Technical Report: Team IIM_TTI
Progressive Recurrent Network for Shadow Removal
Deshadow-Anything: When Segment Anything Model Meets Zero-shot shadow removal
High-Resolution Document Shadow Removal via A Large-Scale Real-World Dataset and A Frequency-Aware Shadow Erasing Net
A Shadow Imaging Bilinear Model and Three-branch Residual Network for Shadow Removal
SAM-helps-Shadow:When Segment Anything Model meet shadow removal
Learning Restoration is Not Enough: Transfering Identical Mapping for Single-Image Shadow Removal
Shadow Removal of Text Document Images Using Background Estimation and Adaptive Text Enhancement
Refusion: Enabling Large-Size Realistic Image Restoration with Latent-Space Diffusion Models
A Decoupled Multi-Task Network for Shadow Removal
Leveraging Inpainting for Single-Image Shadow Removal
ShadowFormer: Global Context Helps Image Shadow Removal
ShadowDiffusion: When Degradation Prior Meets Diffusion Model for Shadow Removal
ShaDocNet: Learning Spatial-Aware Tokens in Transformer for Document Shadow Removal
DeS3: Adaptive Attention-driven Self and Soft Shadow Removal using ViT Similarity
DC-ShadowNet: Single-Image Hard and Soft Shadow Removal Using Unsupervised Domain-Classifier Guided Network
Mask-ShadowNet: Towards Shadow Removal via Masked Adaptive Instance Normalization
Auto-Exposure Fusion for Single-Image Shadow Removal
Self-Supervised Shadow Removal
Robust Graph Learning from Noisy Data
Appearance Harmonization for Single Image Shadow Removal
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.