7 citations · 12 across the 3 of their papers we have counts for
3 papers
cs.CV2024★ 1 cited
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…
cs.CV2023★ 4 cited
Diffusion-Stego: Training-free Diffusion Generative Steganography via Message Projection
Daegyu Kim, Chaehun Shin, Jooyoung Choi +2
Generative steganography is the process of hiding secret messages in generated images instead of cover images. Existing studies on generative steganography use GAN or Flow models t…
cs.CV2023★ 7 cited
Custom-Edit: Text-Guided Image Editing with Customized Diffusion Models
Jooyoung Choi, Yunjey Choi, Yunji Kim +2
Text-to-image diffusion models can generate diverse, high-fidelity images based on user-provided text prompts. Recent research has extended these models to support text-guided imag…