11 papers · 1 filter
CausalChapter: Improving Long-Video Chaptering with Interventional Dependency Modeling
Xinran Duan, Guozhang Li, Yaoyao Zhong +3
Long-form instructional videos require automatic chaptering to support browsing, navigation, and knowledge access. Recent long-context language models can perform chaptering from t…
Breaking Spatial Uniformity: Prior-Guided Mamba with Radial Serialization for Lens Flare Removal
Zijia Fu, Yuanfei Huang, Lizhi Wang +1
Lens flares, caused by complex optical aberrations, severely degrade image quality especially in nighttime photography. Although recent restoration methods have made remarkable pro…
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…
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…
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…
Temporal Residual Guided Diffusion Framework for Event-Driven Video Reconstruction
Lin Zhu, Yunlong Zheng, Yijun Zhang +3
Event-based video reconstruction has garnered increasing attention due to its advantages, such as high dynamic range and rapid motion capture capabilities. However, current methods…
EMatch: A Unified Framework for Event-based Optical Flow and Stereo Matching
Pengjie Zhang, Lin Zhu, Xiao Wang +3
Event cameras have shown promise in vision applications like optical flow estimation and stereo matching, with many specialized architectures leveraging the asynchronous and sparse…
SpikeNeRF: Learning Neural Radiance Fields from Continuous Spike Stream
Lin Zhu, Kangmin Jia, Yifan Zhao +3
Spike cameras, leveraging spike-based integration sampling and high temporal resolution, offer distinct advantages over standard cameras. However, existing approaches reliant on sp…