7 papers
Revealing Latent Information: A Physics-inspired Self-supervised Pre-training Framework for Noisy and Sparse Events
Lin Zhu, Ruonan Liu, Xiao Wang +2
Event camera, a novel neuromorphic vision sensor, records data with high temporal resolution and wide dynamic range, offering new possibilities for accurate visual representation i…
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…
APG-MOS: Auditory Perception Guided-MOS Predictor for Synthetic Speech
Zhicheng Lian, Lizhi Wang, Hua Huang
Automatic speech quality assessment aims to quantify subjective human perception of speech through computational models to reduce the need for labor-consuming manual evaluations. W…
Complementary Advantages: Exploiting Cross-Field Frequency Correlation for NIR-Assisted Image Denoising
Yuchen Wang, Hongyuan Wang, Lizhi Wang +4
Existing single-image denoising algorithms often struggle to restore details when dealing with complex noisy images. The introduction of near-infrared (NIR) images offers new possi…
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…