activity
20192021
most citedAIM 2020 Challenge on Learned Image Signal Processing Pipeline

16 citations · 23 across the 5 of their papers we have counts for

collaborators

10 papers

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.CV2021

Learning for Unconstrained Space-Time Video Super-Resolution

Zhihao Shi, Xiaohong Liu, Chengqi Li +4

Recent years have seen considerable research activities devoted to video enhancement that simultaneously increases temporal frame rate and spatial resolution. However, the existing…

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…

eess.IV2020

AIM 2020 Challenge on Efficient Super-Resolution: Methods and Results

Kai Zhang, Martin Danelljan, Yawei Li +75

This paper reviews the AIM 2020 challenge on efficient single image super-resolution with focus on the proposed solutions and results. The challenge task was to super-resolve an in…

eess.IV20203 cited

AWNet: Attentive Wavelet Network for Image ISP

Linhui Dai, Xiaohong Liu, Chengqi Li +1

As the revolutionary improvement being made on the performance of smartphones over the last decade, mobile photography becomes one of the most common practices among the majority o…

eess.IV2020

Exploit Camera Raw Data for Video Super-Resolution via Hidden Markov Model Inference

Xiaohong Liu, Kangdi Shi, Zhe Wang +1

To the best of our knowledge, the existing deep-learning-based Video Super-Resolution (VSR) methods exclusively make use of videos produced by the Image Signal Processor (ISP) of t…