1 citations · 1 across the 5 of their papers we have counts for
5 papers
STAS: Spatio-Temporal Adaptive Computation Time for Spiking Transformers
Donghwa Kang, Doohyun Kim, Sang-Ki Ko +3
Spiking neural networks (SNNs) offer energy efficiency over artificial neural networks (ANNs) but suffer from high latency and computational overhead due to their multi-timestep op…
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…
CF-DETR: Coarse-to-Fine Transformer for Real-Time Object Detection
Woojin Shin, Donghwa Kang, Byeongyun Park +3
Detection Transformers (DETR) are increasingly adopted in autonomous vehicle (AV) perception systems due to their superior accuracy over convolutional networks. However, concurrent…
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…
AT-SNN: Adaptive Tokens for Vision Transformer on Spiking Neural Network
Donghwa Kang, Youngmoon Lee, Eun-Kyu Lee +3
In the training and inference of spiking neural networks (SNNs), direct training and lightweight computation methods have been orthogonally developed, aimed at reducing power consu…