6 papers
Domain Generalization via Text-Anchored Information Bottleneck
Eunyi Lyou, Yunjeong Choi, Junho Lee +1
Visual recognition models often fail when deployed in new environments. Domain Generalization (DG) addresses this by learning representations that remain invariant to environment-s…
Geometry-Aware Image Flow Matching
Junho Lee, Kwanseok Kim, Joonseok Lee
Recent advances in generative models highlight the power of geometry-aware modeling in manifold-constrained settings. Yet, for natural images, the field remains confined to Euclide…
Is There a Better Source Distribution than Gaussian? Exploring Source Distributions for Image Flow Matching
Junho Lee, Kwanseok Kim, Joonseok Lee
Flow matching has emerged as a powerful generative modeling approach with flexible choices of source distribution. While Gaussian distributions are commonly used, the potential for…
Latent Diffusion Models with Masked AutoEncoders
Junho Lee, Jeongwoo Shin, Hyungwook Choi +1
In spite of the remarkable potential of Latent Diffusion Models (LDMs) in image generation, the desired properties and optimal design of the autoencoders have been underexplored. I…
Scalable Frame Sampling for Video Classification: A Semi-Optimal Policy Approach with Reduced Search Space
Junho Lee, Jeongwoo Shin, Seung Woo Ko +2
Given a video with frames, frame sampling is a task to select frames, so as to maximize the performance of a fixed video classifier. Not just brute-force search, but…
Self-Guided Masked Autoencoder
Jeongwoo Shin, Inseo Lee, Junho Lee +1
Masked Autoencoder (MAE) is a self-supervised approach for representation learning, widely applicable to a variety of downstream tasks in computer vision. In spite of its success,…