2 citations · 2 across the 1 of their papers we have counts for
5 papers · 1 filter
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…
Inspecting Explainability of Transformer Models with Additional Statistical Information
Hoang C. Nguyen, Haeil Lee, Junmo Kim
Transformer becomes more popular in the vision domain in recent years so there is a need for finding an effective way to interpret the Transformer model by visualizing it. In recen…
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…
PBP-Net: Point Projection and Back-Projection Network for 3D Point Cloud Segmentation
JuYoung Yang, Chanho Lee, Pyunghwan Ahn +3
Following considerable development in 3D scanning technologies, many studies have recently been proposed with various approaches for 3D vision tasks, including some methods that ut…