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

16 citations · 27 across the 4 of their papers we have counts for

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6 papers · 1 filter

cs.CV20215 cited

Pseudo Supervised Monocular Depth Estimation with Teacher-Student Network

Huan Liu, Junsong Yuan, Chen Wang +1

Despite recent improvement of supervised monocular depth estimation, the lack of high quality pixel-wise ground truth annotations has become a major hurdle for further progress. In…

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…

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…