144 citations · 747 across the 24 of their papers we have counts for
4 papers · 1 filter
Multi-Attention Based Ultra Lightweight Image Super-Resolution
Abdul Muqeet, Jiwon Hwang, Subin Yang +3
Lightweight image super-resolution (SR) networks have the utmost significance for real-world applications. There are several deep learning based SR methods with remarkable performa…
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…
Towards an Adversarially Robust Normalization Approach
Muhammad Awais, Fahad Shamshad, Sung-Ho Bae
Batch Normalization (BatchNorm) is effective for improving the performance and accelerating the training of deep neural networks. However, it has also shown to be a cause of advers…
SaliencyMix: A Saliency Guided Data Augmentation Strategy for Better Regularization
A. F. M. Shahab Uddin, Mst. Sirazam Monira, Wheemyung Shin +2
Advanced data augmentation strategies have widely been studied to improve the generalization ability of deep learning models. Regional dropout is one of the popular solutions that…