1 citations · 1 across the 8 of their papers we have counts for
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Bidirectional Cross-frequency Domain Interaction Network for UHD Low-Light Image Enhancement
Bo Fu, Hai Chi, Liyan Wang +5
Existing Ultra-High-Definition (UHD) low-light image enhancement (LLIE) methods typically rely on either spatial- or frequency-domain modeling, or independently process different f…
Ultra-High-Definition Restoration Transformers with Correlation Matching Transformation
Cong Wang, Liyan Wang, Jinshan Pan +4
We propose UHDformer++, a general Transformer-based framework to solve numerous Ultra-High-Definition (UHD) image restoration tasks. UHDformer++ operates across coordinated lea…
Degradation-Aware Prompt Learning with Cross-Modal Compensation for Adverse Weather Removal
Wanshu Fan, Yunzhe Zhang, Yue Shen +5
Adverse weather causes diverse and complex image degradations, severely compromising the reliability of computer vision systems. Existing all-in-one restoration models attempt to a…
Neural Discrimination-Prompted Transformers for Efficient UHD Image Restoration and Enhancement
Cong Wang, Jinshan Pan, Liyan Wang +2
We propose a simple yet effective UHDPromer, a neural discrimination-prompted Transformer, for Ultra-High-Definition (UHD) image restoration and enhancement. Our UHDPromer is inspi…
Adapting Large VLMs with Iterative and Manual Instructions for Generative Low-light Enhancement
Xiaoran Sun, Liyan Wang, Yeying Jin +5
Most existing low-light image enhancement (LLIE) methods rely on pre-trained model priors, low-light inputs, or both, while neglecting the semantic guidance available from normal-l…
Deep Learning-Driven Ultra-High-Definition Image Restoration: A Survey
Liyan Wang, Weixiang Zhou, Cong Wang +3
Ultra-high-definition (UHD) image restoration aims to specifically solve the problem of quality degradation in ultra-high-resolution images. Recent advancements in this field are p…
Intra and Inter Parser-Prompted Transformers for Effective Image Restoration
Cong Wang, Jinshan Pan, Liyan Wang +1
We propose Intra and Inter Parser-Prompted Transformers (PPTformer) that explore useful features from visual foundation models for image restoration. Specifically, PPTformer contai…
Ultra-High-Definition Image Restoration: New Benchmarks and A Dual Interaction Prior-Driven Solution
Liyan Wang, Cong Wang, Jinshan Pan +5
Ultra-High-Definition (UHD) image restoration has acquired remarkable attention due to its practical demand. In this paper, we construct UHD snow and rain benchmarks, named UHD-Sno…
How Powerful Potential of Attention on Image Restoration?
Cong Wang, Jinshan Pan, Yeying Jin +5
Transformers have demonstrated their effectiveness in image restoration tasks. Existing Transformer architectures typically comprise two essential components: multi-head self-atten…