13 citations · 20 across the 5 of their papers we have counts for
5 papers
Self-positioning Point-based Transformer for Point Cloud Understanding
Jinyoung Park, Sanghyeok Lee, Sihyeon Kim +2
Transformers have shown superior performance on various computer vision tasks with their capabilities to capture long-range dependencies. Despite the success, it is challenging to…
k-SALSA: k-anonymous synthetic averaging of retinal images via local style alignment
Minkyu Jeon, Hyeonjin Park, Hyunwoo J. Kim +2
The application of modern machine learning to retinal image analyses offers valuable insights into a broad range of human health conditions beyond ophthalmic diseases. Additionally…
SageMix: Saliency-Guided Mixup for Point Clouds
Sanghyeok Lee, Minkyu Jeon, Injae Kim +2
Data augmentation is key to improving the generalization ability of deep learning models. Mixup is a simple and widely-used data augmentation technique that has proven effective in…
Bridging the Gap between Classification and Localization for Weakly Supervised Object Localization
Eunji Kim, Siwon Kim, Jungbeom Lee +2
Weakly supervised object localization aims to find a target object region in a given image with only weak supervision, such as image-level labels. Most existing methods use a class…
Improving Object Detection, Multi-object Tracking, and Re-Identification for Disaster Response Drones
Chongkeun Paik, Hyunwoo J. Kim
We aim to detect and identify multiple objects using multiple cameras and computer vision for disaster response drones. The major challenges are taming detection errors, resolving…