5 papers
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…
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…
Global Attention-Fused Image Cropping with Attention-Guided and Global-Aligned Crop Evaluator
Haotian Yang, Zhile Yang, Kin-Man Lam +2
Image cropping aims to improve image aesthetics by preserving important content within an appropriately composed region. However, most existing methods focus primarily on salient r…
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…