6 papers
Decoupling Variance and Scale-Invariant Updates in Adaptive Gradient Descent for Unified Vector and Matrix Optimization
Zitao Song, Cedar Site Bai, Zhe Zhang +2
Adaptive methods like Adam have become the standard for large-scale vector and Euclidean optimization due to their coordinate-wise adaptation with a second-orde…
WEC-DG: Multi-Exposure Wavelet Correction Method Guided by Degradation Description
Ming Zhao, Pingping Liu, Tongshun Zhang +1
Multi-exposure correction technology is essential for restoring images affected by insufficient or excessive lighting, enhancing the visual experience by improving brightness, cont…
CIVQLLIE: Causal Intervention with Vector Quantization for Low-Light Image Enhancement
Tongshun Zhang, Pingping Liu, Zhe Zhang +1
Images captured in nighttime scenes suffer from severely reduced visibility, hindering effective content perception. Current low-light image enhancement (LLIE) methods face signifi…
CWNet: Causal Wavelet Network for Low-Light Image Enhancement
Tongshun Zhang, Pingping Liu, Yubing Lu +4
Traditional Low-Light Image Enhancement (LLIE) methods primarily focus on uniform brightness adjustment, often neglecting instance-level semantic information and the inherent chara…
ReF-LLE: Personalized Low-Light Enhancement via Reference-Guided Deep Reinforcement Learning
Ming Zhao, Pingping Liu, Tongshun Zhang +1
Low-light image enhancement presents two primary challenges: 1) Significant variations in low-light images across different conditions, and 2) Enhancement levels influenced by subj…
NTIRE 2025 Challenge on HR Depth from Images of Specular and Transparent Surfaces
Pierluigi Zama Ramirez, Fabio Tosi, Luigi Di Stefano +36
This paper reports on the NTIRE 2025 challenge on HR Depth From images of Specular and Transparent surfaces, held in conjunction with the New Trends in Image Restoration and Enhanc…