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12/15/2021
Temporal Shuffling for Defending Deep Action Recognition Models against Adversarial Attacks
Recently, video-based action recognition methods using convolutional neu...
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12/09/2021
Amicable Aid: Turning Adversarial Attack to Benefit Classification
While adversarial attacks on deep image classification models pose serio...
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06/18/2021
Light Lies: Optical Adversarial Attack
A significant amount of work has been done on adversarial attacks that i...
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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...
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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 ...
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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...
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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...
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06/02/2020
SRZoo: An integrated repository for super-resolution using deep learning
Deep learning-based image processing algorithms, including image super-r...
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04/29/2020
EmbraceNet for Activity: A Deep Multimodal Fusion Architecture for Activity Recognition
Human activity recognition using multiple sensors is a challenging but p...
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04/19/2019
EmbraceNet: A robust deep learning architecture for multimodal classification
Classification using multimodal data arises in many machine learning app...
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04/12/2019
Evaluating Robustness of Deep Image Super-Resolution against Adversarial Attacks
Single-image super-resolution aims to generate a high-resolution version...
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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...
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11/29/2018
RAM: Residual Attention Module for Single Image Super-Resolution
Attention mechanisms are a design trend of deep neural networks that sta...
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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...
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09/13/2018
Generative adversarial network-based image super-resolution using perceptual content losses
In this paper, we propose a deep generative adversarial network for supe...
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09/29/2017