32 citations · 73 across the 10 of their papers we have counts for
4 papers · 1 filter
GuidedMixup: An Efficient Mixup Strategy Guided by Saliency Maps
Minsoo Kang, Suhyun Kim
Data augmentation is now an essential part of the image training process, as it effectively prevents overfitting and makes the model more robust against noisy datasets. Recent mixi…
Conditional Score Guidance for Text-Driven Image-to-Image Translation
Hyunsoo Lee, Minsoo Kang, Bohyung Han
We present a novel algorithm for text-driven image-to-image translation based on a pretrained text-to-image diffusion model. Our method aims to generate a target image by selective…
Variational Distribution Learning for Unsupervised Text-to-Image Generation
Minsoo Kang, Doyup Lee, Jiseob Kim +2
We propose a text-to-image generation algorithm based on deep neural networks when text captions for images are unavailable during training. In this work, instead of simply generat…
Information-Theoretic GAN Compression with Variational Energy-based Model
Minsoo Kang, Hyewon Yoo, Eunhee Kang +3
We propose an information-theoretic knowledge distillation approach for the compression of generative adversarial networks, which aims to maximize the mutual information between te…