10 citations · 10 across the 3 of their papers we have counts for
3 papers
cs.LG2024
ACDC: Autoregressive Coherent Multimodal Generation using Diffusion Correction
Hyungjin Chung, Dohun Lee, Jong Chul Ye
Autoregressive models (ARMs) and diffusion models (DMs) represent two leading paradigms in generative modeling, each excelling in distinct areas: ARMs in global context modeling an…
cs.LG2024★ 10 cited
A Survey on Diffusion Models for Inverse Problems
Giannis Daras, Hyungjin Chung, Chieh-Hsin Lai +5
Diffusion models have become increasingly popular for generative modeling due to their ability to generate high-quality samples. This has unlocked exciting new possibilities for so…
eess.IV2024
Fundus image enhancement through direct diffusion bridges
Sehui Kim, Hyungjin Chung, Se Hie Park +3
We propose FD3, a fundus image enhancement method based on direct diffusion bridges, which can cope with a wide range of complex degradations, including haze, blur, noise, and shad…