research
∙
08/19/2022
Demystifying Randomly Initialized Networks for Evaluating Generative Models
Evaluation of generative models is mostly based on the comparison betwee...
share
research
∙
04/30/2021
Deep Image Destruction: A Comprehensive Study on Vulnerability of Deep Image-to-Image Models against Adversarial Attacks
Recently, the vulnerability of deep image classification models to adver...
research
∙
11/30/2020
Just One Moment: Inconspicuous One Frame Attack on Deep Action Recognition
The video-based action recognition task has been extensively studied in ...
research
∙
09/25/2020
AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results
This paper introduces the real image Super-Resolution (SR) challenge tha...
research
∙
09/15/2020
AIM 2020 Challenge on Efficient Super-Resolution: Methods and Results
This paper reviews the AIM 2020 challenge on efficient single image supe...
research
∙
06/02/2020
SRZoo: An integrated repository for super-resolution using deep learning
Deep learning-based image processing algorithms, including image super-r...
research
∙
04/12/2019
Evaluating Robustness of Deep Image Super-Resolution against Adversarial Attacks
Single-image super-resolution aims to generate a high-resolution version...
research
∙
11/30/2018
Lightweight and Efficient Image Super-Resolution with Block State-based Recursive Network
Recently, several deep learning-based image super-resolution methods hav...
research
∙
11/29/2018
RAM: Residual Attention Module for Single Image Super-Resolution
Attention mechanisms are a design trend of deep neural networks that sta...
research
∙
09/13/2018
Deep Learning-based Image Super-Resolution Considering Quantitative and Perceptual Quality
Recently, it has been shown that in super-resolution, there exists a tra...
research
∙
09/13/2018