4 citations · 5 across the 11 of their papers we have counts for
10 papers · 1 filter
ST-DiffEye: Diffusion-based Continuous Gaze Generation via Joint Scanpath-Trajectory Modeling
Brian Nlong Zhao, Ozgur Kara, Junho Kim +1
We study the problem of human gaze modeling, which aims to generate the gaze patterns a viewer produces while observing a visual stimulus. Gaze is primarily captured through two mo…
Grounding World Simulation Models in a Real-World Metropolis
Junyoung Seo, Hyunwook Choi, Minkyung Kwon +10
What if a world simulation model could render not an imagined environment but a city that actually exists? Prior generative world models synthesize visually plausible yet artificia…
Pygmalion Effect in Vision: Image-to-Clay Translation for Reflective Geometry Reconstruction
Gayoung Lee, Junho Kim, Jin-Hwa Kim +1
Understanding reflection remains a long-standing challenge in 3D reconstruction due to the entanglement of appearance and geometry under view-dependent reflections. In this work, w…
StyleKeeper: Prevent Content Leakage using Negative Visual Query Guidance
Jaeseok Jeong, Junho Kim, Gayoung Lee +2
In the domain of text-to-image generation, diffusion models have emerged as powerful tools. Recently, studies on visual prompting, where images are used as prompts, have enabled mo…
Aligned Novel View Image and Geometry Synthesis via Cross-modal Attention Instillation
Min-Seop Kwak, Junho Kim, Sangdoo Yun +4
We introduce a diffusion-based framework that performs aligned novel view image and geometry generation via a warping-and-inpainting methodology. Unlike prior methods that require…
Enhancing Creative Generation on Stable Diffusion-based Models
Jiyeon Han, Dahee Kwon, Gayoung Lee +2
Recent text-to-image generative models, particularly Stable Diffusion and its distilled variants, have achieved impressive fidelity and strong text-image alignment. However, their…
DECOR:Decomposition and Projection of Text Embeddings for Text-to-Image Customization
Geonhui Jang, Jin-Hwa Kim, Yong-Hyun Park +3
Text-to-image (T2I) models can effectively capture the content or style of reference images to perform high-quality customization. A representative technique for this is fine-tunin…
Direct Unlearning Optimization for Robust and Safe Text-to-Image Models
Yong-Hyun Park, Sangdoo Yun, Jin-Hwa Kim +5
Recent advancements in text-to-image (T2I) models have unlocked a wide range of applications but also present significant risks, particularly in their potential to generate unsafe…
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…
Sequential Data Generation with Groupwise Diffusion Process
Sangyun Lee, Gayoung Lee, Hyunsu Kim +2
We present the Groupwise Diffusion Model (GDM), which divides data into multiple groups and diffuses one group at one time interval in the forward diffusion process. GDM generates…