4 citations · 5 across the 6 of their papers we have counts for
6 papers
LayeringDiff: Layered Image Synthesis via Generation, then Disassembly with Generative Knowledge
Kyoungkook Kang, Gyujin Sim, Geonung Kim +3
Layers have become indispensable tools for professional artists, allowing them to build a hierarchical structure that enables independent control over individual visual elements. I…
SAFIRE: Segment Any Forged Image Region
Myung-Joon Kwon, Wonjun Lee, Seung-Hun Nam +2
Most techniques approach the problem of image forgery localization as a binary segmentation task, training neural networks to label original areas as 0 and forged areas as 1. In co…
Nearly Zero-Cost Protection Against Mimicry by Personalized Diffusion Models
Namhyuk Ahn, KiYoon Yoo, Wonhyuk Ahn +2
Recent advancements in diffusion models revolutionize image generation but pose risks of misuse, such as replicating artworks or generating deepfakes. Existing image protection met…
Imperceptible Protection against Style Imitation from Diffusion Models
Namhyuk Ahn, Wonhyuk Ahn, KiYoon Yoo +2
Recent progress in diffusion models has profoundly enhanced the fidelity of image generation, but it has raised concerns about copyright infringements. While prior methods have int…
DreamStyler: Paint by Style Inversion with Text-to-Image Diffusion Models
Namhyuk Ahn, Junsoo Lee, Chunggi Lee +4
Recent progresses in large-scale text-to-image models have yielded remarkable accomplishments, finding various applications in art domain. However, expressing unique characteristic…
CoVA: Exploiting Compressed-Domain Analysis to Accelerate Video Analytics
Jinwoo Hwang, Minsu Kim, Daeun Kim +5
Modern retrospective analytics systems leverage cascade architecture to mitigate bottleneck for computing deep neural networks (DNNs). However, the existing cascades suffer two lim…