10 citations · 12 across the 6 of their papers we have counts for
6 papers
UR2P-Dehaze: Learning a Simple Image Dehaze Enhancer via Unpaired Rich Physical Prior
Minglong Xue, Shuaibin Fan, Shivakumara Palaiahnakote +1
Image dehazing techniques aim to enhance contrast and restore details, which are essential for preserving visual information and improving image processing accuracy. Existing metho…
Unified Image Restoration and Enhancement: Degradation Calibrated Cycle Reconstruction Diffusion Model
Minglong Xue, Jinhong He, Shivakumara Palaiahnakote +1
Image restoration and enhancement are pivotal for numerous computer vision applications, yet unifying these tasks efficiently remains a significant challenge. Inspired by the itera…
Zero-Shot Low-Light Image Enhancement via Joint Frequency Domain Priors Guided Diffusion
Jinhong He, Shivakumara Palaiahnakote, Aoxiang Ning +1
Due to the singularity of real-world paired datasets and the complexity of low-light environments, this leads to supervised methods lacking a degree of scene generalisation. Meanwh…
Optimizing 4D Lookup Table for Low-light Video Enhancement via Wavelet Priori
Jinhong He, Minglong Xue, Wenhai Wang +1
Low-light video enhancement is highly demanding in maintaining spatiotemporal color consistency. Therefore, improving the accuracy of color mapping and keeping the latency low is c…
Zero-Reference Lighting Estimation Diffusion Model for Low-Light Image Enhancement
Jinhong He, Minglong Xue, Aoxiang Ning +1
Diffusion model-based low-light image enhancement methods rely heavily on paired training data, leading to limited extensive application. Meanwhile, existing unsupervised methods l…
Low-light Image Enhancement via CLIP-Fourier Guided Wavelet Diffusion
Minglong Xue, Jinhong He, Wenhai Wang +1
Low-light image enhancement techniques have significantly progressed, but unstable image quality recovery and unsatisfactory visual perception are still significant challenges. To…