23 citations · 49 across the 14 of their papers we have counts for
4 papers · 1 filter
Large-Scale Text-to-Image Model with Inpainting is a Zero-Shot Subject-Driven Image Generator
Chaehun Shin, Jooyoung Choi, Heeseung Kim +1
Subject-driven text-to-image generation aims to produce images of a new subject within a desired context by accurately capturing both the visual characteristics of the subject and…
Style-Friendly SNR Sampler for Style-Driven Generation
Jooyoung Choi, Chaehun Shin, Yeongtak Oh +3
Recent text-to-image diffusion models generate high-quality images but struggle to learn new, personalized styles, which limits the creation of unique style templates. In style-dri…
Disentangled Motion Modeling for Video Frame Interpolation
Jaihyun Lew, Jooyoung Choi, Chaehun Shin +2
Video Frame Interpolation (VFI) aims to synthesize intermediate frames between existing frames to enhance visual smoothness and quality. Beyond the conventional methods based on th…
Improving Diffusion-Based Generative Models via Approximated Optimal Transport
Daegyu Kim, Jooyoung Choi, Chaehun Shin +2
We introduce the Approximated Optimal Transport (AOT) technique, a novel training scheme for diffusion-based generative models. Our approach aims to approximate and integrate optim…