62 citations · 203 across the 19 of their papers we have counts for
6 papers · 1 filter
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…
GIA-Net: Global Information Aware Network for Low-light Imaging
Zibo Meng, Runsheng Xu, Chiu Man Ho
It is extremely challenging to acquire perceptually plausible images under low-light conditions due to low SNR. Most recently, U-Nets have shown promising results for low-light ima…
Point Adversarial Self Mining: A Simple Method for Facial Expression Recognition
Ping Liu, Yuewei Lin, Zibo Meng +4
In this paper, we propose a simple yet effective approach, named Point Adversarial Self Mining (PASM), to improve the recognition accuracy in facial expression recognition. Unlike…
NTIRE 2020 Challenge on Real-World Image Super-Resolution: Methods and Results
Andreas Lugmayr, Martin Danelljan, Radu Timofte +43
This paper reviews the NTIRE 2020 challenge on real world super-resolution. It focuses on the participating methods and final results. The challenge addresses the real world settin…
Omni-supervised Facial Expression Recognition via Distilled Data
Ping Liu, Yunchao Wei, Zibo Meng +3
Facial expression plays an important role in understanding human emotions. Most recently, deep learning based methods have shown promising for facial expression recognition. Howeve…
Residual Channel Attention Generative Adversarial Network for Image Super-Resolution and Noise Reduction
Jie Cai, Zibo Meng, Chiu Man Ho
Image super-resolution is one of the important computer vision techniques aiming to reconstruct high-resolution images from corresponding low-resolution ones. Most recently, deep l…