5 papers · 1 filter
Multi-Modal Object Re-Identification with Dual Semantic Guidance and Global-Local Mutual Modulation
Weixiang Zhou, Xingguo Xu, Yuhao Wang +4
Multi-modal object Re-Identification (ReID) aims to retrieve target instances by leveraging complementary information across modalities. However, existing methods suffer from two c…
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…
Noise Calibration: Plug-and-play Content-Preserving Video Enhancement using Pre-trained Video Diffusion Models
Qinyu Yang, Haoxin Chen, Yong Zhang +4
In order to improve the quality of synthesized videos, currently, one predominant method involves retraining an expert diffusion model and then implementing a noising-denoising pro…
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…