activity
20202026
most citedRethinking Performance Gains in Image Dehazing Networks

48 citations · 50 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2026

Fast Low-light Enhancement and Deblurring for 3D Dark Scenes

Feng Zhang, Jinglong Wang, Ze Li +4

Novel view synthesis from low-light, noisy, and motion-blurred imagery remains a valuable and challenging task. Current volumetric rendering methods struggle with compound degradat…

cs.CV2022

ClassPruning: Speed Up Image Restoration Networks by Dynamic N:M Pruning

Yang Zhou, Yuda Song, Hui Qian +1

Image restoration tasks have achieved tremendous performance improvements with the rapid advancement of deep neural networks. However, most prevalent deep learning models perform i…

eess.IV2022★ 2 cited

Modular Degradation Simulation and Restoration for Under-Display Camera

Yang Zhou, Yuda Song, Xin Du

Under-display camera (UDC) provides an elegant solution for full-screen smartphones. However, UDC captured images suffer from severe degradation since sensors lie under the display…

cs.CV2022★ 48 cited

Rethinking Performance Gains in Image Dehazing Networks

Yuda Song, Yang Zhou, Hui Qian +1

Image dehazing is an active topic in low-level vision, and many image dehazing networks have been proposed with the rapid development of deep learning. Although these networks' pip…

cs.CV2020

End-To-End Trainable Video Super-Resolution Based on a New Mechanism for Implicit Motion Estimation and Compensation

Xiaohong Liu, Lingshi Kong, Yang Zhou +2

Video super-resolution aims at generating a high-resolution video from its low-resolution counterpart. With the rapid rise of deep learning, many recently proposed video super-reso…