7 citations · 8 across the 11 of their papers we have counts for
5 papers · 1 filter
Fluently Lying: Adversarial Robustness Can Be Substrate-Dependent
Daye Kang, Hyeongboo Baek
The primary tools used to monitor and defend object detectors under adversarial attack assume that when accuracy degrades, detection count drops in tandem. This coupling was assume…
Timestep-Compressed Attack on Spiking Neural Networks through Timestep-Level Backpropagation
Donghwa Kang, Doohyun Kim, Sang-Ki Ko +3
State-of-the-art (SOTA) gradient-based adversarial attacks on spiking neural networks (SNNs), which largely rely on extending FGSM and PGD frameworks, face a critical limitation: s…
A 2-Stage Model for Vehicle Class and Orientation Detection with Photo-Realistic Image Generation
Youngmin Kim, Donghwa Kang, Hyeongboo Baek
We aim to detect the class and orientation of a vehicle by training a model with synthetic data. However, the distribution of the classes in the training data is imbalanced, and th…
BankTweak: Adversarial Attack against Multi-Object Trackers by Manipulating Feature Banks
Woojin Shin, Donghwa Kang, Daejin Choi +3
Multi-object tracking (MOT) aims to construct moving trajectories for objects, and modern multi-object trackers mainly utilize the tracking-by-detection methodology. Initial approa…
Keypoint based Sign Language Translation without Glosses
Youngmin Kim, Minji Kwak, Dain Lee +2
Sign Language Translation (SLT) is a task that has not been studied relatively much compared to the study of Sign Language Recognition (SLR). However, the SLR is a study that recog…