most citedNoise Map Guidance: Inversion with Spatial Context for Real Image Editing

1 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

cs.AI2025

PICKT: Practical Interlinked Concept Knowledge Tracing for Personalized Learning using Knowledge Map Concept Relations

Wonbeen Lee, Channyoung Lee, Junho Sohn +1

With the recent surge in personalized learning, Intelligent Tutoring Systems (ITS) that can accurately track students' individual knowledge states and provide tailored learning pat…

cs.CV2025

Improving Diffusion-Based Image Editing Faithfulness via Guidance and Scheduling

Hansam Cho, Seoung Bum Kim

Text-guided diffusion models have become essential for high-quality image synthesis, enabling dynamic image editing. In image editing, two crucial aspects are editability, which de…

cs.CV2024

One-Shot Structure-Aware Stylized Image Synthesis

Hansam Cho, Jonghyun Lee, Seunggyu Chang +1

While GAN-based models have been successful in image stylization tasks, they often struggle with structure preservation while stylizing a wide range of input images. Recently, diff…

cs.CV20241 cited

Noise Map Guidance: Inversion with Spatial Context for Real Image Editing

Hansam Cho, Jonghyun Lee, Seoung Bum Kim +2

Text-guided diffusion models have become a popular tool in image synthesis, known for producing high-quality and diverse images. However, their application to editing real images o…

cs.CV20241 cited

Compose and Conquer: Diffusion-Based 3D Depth Aware Composable Image Synthesis

Jonghyun Lee, Hansam Cho, Youngjoon Yoo +2

Addressing the limitations of text as a source of accurate layout representation in text-conditional diffusion models, many works incorporate additional signals to condition certai…