23 citations · 52 across the 13 of their papers we have counts for
7 papers · 1 filter
Align Your Tangent: Training Better Consistency Models via Manifold-Aligned Tangents
Beomsu Kim, Byunghee Cha, Jong Chul Ye
With diffusion and flow matching models achieving state-of-the-art generating performance, the interest of the community now turned to reducing the inference time without sacrifici…
Latent Schrodinger Bridge: Prompting Latent Diffusion for Fast Unpaired Image-to-Image Translation
Jeongsol Kim, Beomsu Kim, Jong Chul Ye
Diffusion models (DMs), which enable both image generation from noise and inversion from data, have inspired powerful unpaired image-to-image (I2I) translation algorithms. However,…
Generalized Consistency Trajectory Models for Image Manipulation
Beomsu Kim, Jaemin Kim, Jeongsol Kim +1
Diffusion models (DMs) excel in unconditional generation, as well as on applications such as image editing and restoration. The success of DMs lies in the iterative nature of diffu…
Energy-Based Cross Attention for Bayesian Context Update in Text-to-Image Diffusion Models
Geon Yeong Park, Jeongsol Kim, Beomsu Kim +2
Despite the remarkable performance of text-to-image diffusion models in image generation tasks, recent studies have raised the issue that generated images sometimes cannot capture…
Unpaired Image-to-Image Translation via Neural Schrödinger Bridge
Beomsu Kim, Gihyun Kwon, Kwanyoung Kim +1
Diffusion models are a powerful class of generative models which simulate stochastic differential equations (SDEs) to generate data from noise. While diffusion models have achieved…
Disentangling Label Distribution for Long-tailed Visual Recognition
Youngkyu Hong, Seungju Han, Kwanghee Choi +3
The current evaluation protocol of long-tailed visual recognition trains the classification model on the long-tailed source label distribution and evaluates its performance on the…