35 citations · 96 across the 13 of their papers we have counts for
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cs.CV2025
Measuring and Controlling the Spectral Bias for Self-Supervised Image Denoising
Wang Zhang, Huaqiu Li, Xiaowan Hu +3
Current self-supervised denoising methods for paired noisy images typically involve mapping one noisy image through the network to the other noisy image. However, after measuring t…
cs.CV2025
Interpretable Unsupervised Joint Denoising and Enhancement for Real-World low-light Scenarios
Huaqiu Li, Xiaowan Hu, Haoqian Wang
Real-world low-light images often suffer from complex degradations such as local overexposure, low brightness, noise, and uneven illumination. Supervised methods tend to overfit to…
cs.CV2025
Prompt-SID: Learning Structural Representation Prompt via Latent Diffusion for Single-Image Denoising
Huaqiu Li, Wang Zhang, Xiaowan Hu +3
Many studies have concentrated on constructing supervised models utilizing paired datasets for image denoising, which proves to be expensive and time-consuming. Current self-superv…