activity
20182021
most citedAIM 2020 Challenge on Learned Image Signal Processing Pipeline

16 citations · 22 across the 3 of their papers we have counts for

collaborators

5 papers

eess.IV20215 cited

A Two-branch Neural Network for Non-homogeneous Dehazing via Ensemble Learning

Yankun Yu, Huan Liu, Minghan Fu +3

Recently, there has been rapid and significant progress on image dehazing. Many deep learning based methods have shown their superb performance in handling homogeneous dehazing pro…

cs.CV20211 cited

Towards a Unified Approach to Single Image Deraining and Dehazing

Xiaohong Liu, Yongrui Ma, Zhihao Shi +2

We develop a new physical model for the rain effect and show that the well-known atmosphere scattering model (ASM) for the haze effect naturally emerges as its homogeneous continuo…

cs.CV202016 cited

AIM 2020 Challenge on Learned Image Signal Processing Pipeline

Andrey Ignatov, Radu Timofte, Zhilu Zhang +36

This paper reviews the second AIM learned ISP challenge and provides the description of the proposed solutions and results. The participating teams were solving a real-world RAW-to…

cs.CV2018

Generic Model-Agnostic Convolutional Neural Network for Single Image Dehazing

Zheng Liu, Botao Xiao, Muhammad Alrabeiah +2

Haze and smog are among the most common environmental factors impacting image quality and, therefore, image analysis. This paper proposes an end-to-end generative method for image…

cs.CV2018

Action Recognition for Depth Video using Multi-view Dynamic Images

Yang Xiao, Jun Chen, Yancheng Wang +3

Dynamic imaging is a recently proposed action description paradigm for simultaneously capturing motion and temporal evolution information, particularly in the context of deep convo…