activity
20172020
most citedBridging Adversarial Robustness and Gradient Interpretability

26 citations · 36 across the 3 of their papers we have counts for

collaborators

7 papers

eess.IV20209 cited

NTIRE 2020 Challenge on Perceptual Extreme Super-Resolution: Methods and Results

Kai Zhang, Shuhang Gu, Radu Timofte +60

This paper reviews the NTIRE 2020 challenge on perceptual extreme super-resolution with focus on proposed solutions and results. The challenge task was to super-resolve an input im…

cs.CV2019

Deep Closed-Form Subspace Clustering

Junghoon Seo, Jamyoung Koo, Taegyun Jeon

We propose Deep Closed-Form Subspace Clustering (DCFSC), a new embarrassingly simple model for subspace clustering with learning non-linear mapping. Compared with the previous deep…

cs.LG2019

NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations

Yooseung Wang, Junghoon Seo, Taegyun Jeon

Road extraction from very high resolution satellite (VHR) images is one of the most important topics in the field of remote sensing. In this paper, we propose an efficient Non-Loca…

cs.LG201926 cited

Bridging Adversarial Robustness and Gradient Interpretability

Beomsu Kim, Junghoon Seo, Taegyun Jeon

Adversarial training is a training scheme designed to counter adversarial attacks by augmenting the training dataset with adversarial examples. Surprisingly, several studies have o…

cs.LG2019

Why are Saliency Maps Noisy? Cause of and Solution to Noisy Saliency Maps

Beomsu Kim, Junghoon Seo, SeungHyun Jeon +3

Saliency Map, the gradient of the score function with respect to the input, is the most basic technique for interpreting deep neural network decisions. However, saliency maps are o…

cs.CV2018

Domain Adaptive Generation of Aircraft on Satellite Imagery via Simulated and Unsupervised Learning

Junghoon Seo, Seunghyun Jeon, Taegyun Jeon

Object detection and classification for aircraft are the most important tasks in the satellite image analysis. The success of modern detection and classification methods has been b…