7 citations · 19 across the 7 of their papers we have counts for
7 papers
Visual Style Prompting with Swapping Self-Attention
Jaeseok Jeong, Junho Kim, Yunjey Choi +2
In the evolving domain of text-to-image generation, diffusion models have emerged as powerful tools in content creation. Despite their remarkable capability, existing models still…
User-friendly Image Editing with Minimal Text Input: Leveraging Captioning and Injection Techniques
Sunwoo Kim, Wooseok Jang, Hyunsu Kim +4
Recent text-driven image editing in diffusion models has shown remarkable success. However, the existing methods assume that the user's description sufficiently grounds the context…
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…
Learning Input-agnostic Manipulation Directions in StyleGAN with Text Guidance
Yoonjeon Kim, Hyunsu Kim, Junho Kim +2
With the advantages of fast inference and human-friendly flexible manipulation, image-agnostic style manipulation via text guidance enables new applications that were not previousl…
Generator Knows What Discriminator Should Learn in Unconditional GANs
Gayoung Lee, Hyunsu Kim, Junho Kim +3
Recent methods for conditional image generation benefit from dense supervision such as segmentation label maps to achieve high-fidelity. However, it is rarely explored to employ de…
Memory Efficient Patch-based Training for INR-based GANs
Namwoo Lee, Hyunsu Kim, Gayoung Lee +2
Recent studies have shown remarkable progress in GANs based on implicit neural representation (INR) - an MLP that produces an RGB value given its (x, y) coordinate. They represent…