7 papers
UHD-GPGNet: UHD Video Denoising via Gaussian-Process-Guided Local Spatio-Temporal Modeling
Weiyuan He, Chen Wu, Pengwen Dai +6
Ultra-high-definition (UHD) video denoising requires simultaneously suppressing complex spatio-temporal degradations, preserving fine textures and chromatic stability, and maintain…
Laplace-Mamba: Laplace Frequency Prior-Guided Mamba-CNN Fusion Network for Image Dehazing
Yongzhen Wang, Liangliang Chen, Bingwen Hu +3
Recent progress in image restoration has underscored Spatial State Models (SSMs) as powerful tools for modeling long-range dependencies, owing to their appealing linear complexity…
M2Restore: Mixture-of-Experts-based Mamba-CNN Fusion Framework for All-in-One Image Restoration
Yongzhen Wang, Yongjun Li, Zhuoran Zheng +2
Natural images are often degraded by complex, composite degradations such as rain, snow, and haze, which adversely impact downstream vision applications. While existing image resto…
WDMamba: When Wavelet Degradation Prior Meets Vision Mamba for Image Dehazing
Jie Sun, Heng Liu, Yongzhen Wang +2
In this paper, we reveal a novel haze-specific wavelet degradation prior observed through wavelet transform analysis, which shows that haze-related information predominantly reside…
DA2Diff: Exploring Degradation-aware Adaptive Diffusion Priors for All-in-One Weather Restoration
Jiamei Xiong, Xuefeng Yan, Yongzhen Wang +3
Image restoration under adverse weather conditions is a critical task for many vision-based applications. Recent all-in-one frameworks that handle multiple weather degradations wit…
FriendNet: Detection-Friendly Dehazing Network
Yihua Fan, Yongzhen Wang, Mingqiang Wei +2
Adverse weather conditions often impair the quality of captured images, inevitably inducing cutting-edge object detection models for advanced driver assistance systems (ADAS) and a…