25 citations · 36 across the 6 of their papers we have counts for
6 papers
ESGCN: Edge Squeeze Attention Graph Convolutional Network for Traffic Flow Forecasting
Sangrok Lee, Ha Young Kim
Traffic forecasting is a highly challenging task owing to the dynamical spatio-temporal dependencies of traffic flows. To handle this, we focus on modeling the spatio-temporal dyna…
Decompose, Adjust, Compose: Effective Normalization by Playing with Frequency for Domain Generalization
Sangrok Lee, Jongseong Bae, Ha Young Kim
Domain generalization (DG) is a principal task to evaluate the robustness of computer vision models. Many previous studies have used normalization for DG. In normalization, statist…
SBNet: Segmentation-based Network for Natural Language-based Vehicle Search
Sangrok Lee, Taekang Woo, Sang Hun Lee
Natural language-based vehicle retrieval is a task to find a target vehicle within a given image based on a natural language description as a query. This technology can be applied…
Multi-Attention-Based Soft Partition Network for Vehicle Re-Identification
Sangrok Lee, Taekang Woo, Sang Hun Lee
Vehicle re-identification helps in distinguishing between images of the same and other vehicles. It is a challenging process because of significant intra-instance differences betwe…
StRDAN: Synthetic-to-Real Domain Adaptation Network for Vehicle Re-Identification
Sangrok Lee, Eunsoo Park, Hongsuk Yi +1
Vehicle re-identification aims to obtain the same vehicles from vehicle images. This is challenging but essential for analyzing and predicting traffic flow in the city. Although de…
An Energy and GPU-Computation Efficient Backbone Network for Real-Time Object Detection
Youngwan Lee, Joong-won Hwang, Sangrok Lee +2
As DenseNet conserves intermediate features with diverse receptive fields by aggregating them with dense connection, it shows good performance on the object detection task. Althoug…