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Daesik Kim

5 papers hereh-index 477 citations6 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author5

Across the 5 of 5 papers where every author was matched, so the position is known.

fields
  • cs.CV4
  • cs.MM1
same name
  • Daesik Kim — 10 papers, h 9
  • Daesik Kim — 2 papers, h 2
  • Daesik Kim — 1 paper, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20202024
most citedDiffBlender: Composable and Versatile Multimodal Text-to-Image Diffusion Models

3 citations · 7 across the 5 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2024

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…

cs.CV2024★ 1 cited

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…

cs.CV2023

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…

cs.CV2023★ 3 cited

DiffBlender: Composable and Versatile Multimodal Text-to-Image Diffusion Models

Sungnyun Kim, Junsoo Lee, Kibeom Hong +2

In this study, we aim to enhance the capabilities of diffusion-based text-to-image (T2I) generation models by integrating diverse modalities beyond textual descriptions within a un…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.