5 papers
Bridging the Manifold Gap: Riemannian Residual Line Search for One-Step Image Editing
Hongzhu Yi, Zhongtian Luo, Tong Li +2
One-step diffusion editors are fast because they avoid inversion and iterative optimization, but a single transport update must be aggressive enough to realize the target prompt an…
Rethinking Model Redundancy for Low-light Image Enhancement
Tong Li, Lizhi Wang, Hansen Feng +3
Low-light image enhancement (LLIE) is a fundamental task in computational photography, aiming to improve illumination, reduce noise, and enhance the image quality of low-light imag…
YOND: Practical Blind Raw Image Denoising Free from Camera-Specific Data Dependency
Hansen Feng, Lizhi Wang, Yiqi Huang +3
The rapid advancement of photography has created a growing demand for a practical blind raw image denoising method. Recently, learning-based methods have become mainstream due to t…
PDE: Gene Effect Inspired Parameter Dynamic Evolution for Low-light Image Enhancement
Tong Li, Lizhi Wang, Hansen Feng +2
Low-light image enhancement (LLIE) is a fundamental task in computational photography, aiming to improve illumination, reduce noise, and enhance image quality. While recent advance…
Positive2Negative: Breaking the Information-Lossy Barrier in Self-Supervised Single Image Denoising
Tong Li, Lizhi Wang, Zhiyuan Xu +3
Image denoising enhances image quality, serving as a foundational technique across various computational photography applications. The obstacle to clean image acquisition in real s…