6 citations · 14 across the 6 of their papers we have counts for
7 papers
DeFloMat: Detection with Flow Matching for Stable and Efficient Generative Object Localization
Hansang Lee, Chaelin Lee, Nieun Seo +2
We propose DeFloMat (Detection with Flow Matching), a novel generative object detection framework that addresses the critical latency bottleneck of diffusion-based detectors, such…
Beta Sampling is All You Need: Efficient Image Generation Strategy for Diffusion Models using Stepwise Spectral Analysis
Haeil Lee, Hansang Lee, Seoyeon Gye +1
Generative diffusion models have emerged as a powerful tool for high-quality image synthesis, yet their iterative nature demands significant computational resources. This paper pro…
GenMix: Combining Generative and Mixture Data Augmentation for Medical Image Classification
Hansang Lee, Haeil Lee, Helen Hong
In this paper, we propose a novel data augmentation technique called GenMix, which combines generative and mixture approaches to leverage the strengths of both methods. While gener…
The Effects of Mixed Sample Data Augmentation are Class Dependent
Haeil Lee, Hansang Lee, Junmo Kim
Mixed Sample Data Augmentation (MSDA) techniques, such as Mixup, CutMix, and PuzzleMix, have been widely acknowledged for enhancing performance in a variety of tasks. A previous st…
Noisy Label Classification using Label Noise Selection with Test-Time Augmentation Cross-Entropy and NoiseMix Learning
Hansang Lee, Haeil Lee, Helen Hong +1
As the size of the dataset used in deep learning tasks increases, the noisy label problem, which is a task of making deep learning robust to the incorrectly labeled data, has becom…
Why Do Deep Neural Networks Still Not Recognize These Images?: A Qualitative Analysis on Failure Cases of ImageNet Classification
Han S. Lee, Alex A. Agarwal, Junmo Kim
In a recent decade, ImageNet has become the most notable and powerful benchmark database in computer vision and machine learning community. As ImageNet has emerged as a representat…
Do Vision Models Encode Object-Level Semantic Relatedness? A Cognitive Psychology-Inspired Benchmark
Hansang Lee, Haeil Lee, Junmo Kim
Modern vision models have achieved strong object-recognition performance, yet it remains unclear whether their representations encode object-level semantic relatedness, the meaning…