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20212026
most citedExploiting Cultural Biases via Homoglyphs in Text-to-Image Synthesis

34 citations · 212 across the 70 of their papers we have counts for

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Showing 2023 · cs.CVShow all

5 papers · 2 filters

cs.CV2023

LEDITS++: Limitless Image Editing using Text-to-Image Models

Manuel Brack, Felix Friedrich, Katharina Kornmeier +4

Text-to-image diffusion models have recently received increasing interest for their astonishing ability to produce high-fidelity images from solely text inputs. Subsequent research…

cs.CV2023

Distilling Adversarial Prompts from Safety Benchmarks: Report for the Adversarial Nibbler Challenge

Manuel Brack, Patrick Schramowski, Kristian Kersting

Text-conditioned image generation models have recently achieved astonishing image quality and alignment results. Consequently, they are employed in a fast-growing number of applica…

cs.CV2023★ 5 cited

Mitigating Inappropriateness in Image Generation: Can there be Value in Reflecting the World's Ugliness?

Manuel Brack, Felix Friedrich, Patrick Schramowski +1

Text-conditioned image generation models have recently achieved astonishing results in image quality and text alignment and are consequently employed in a fast-growing number of ap…

cs.CV2023★ 6 cited

MultiFusion: Fusing Pre-Trained Models for Multi-Lingual, Multi-Modal Image Generation

Marco Bellagente, Manuel Brack, Hannah Teufel +11

The recent popularity of text-to-image diffusion models (DM) can largely be attributed to the intuitive interface they provide to users. The intended generation can be expressed in…

cs.CV2023★ 12 cited

SEGA: Instructing Text-to-Image Models using Semantic Guidance

Manuel Brack, Felix Friedrich, Dominik Hintersdorf +3

Text-to-image diffusion models have recently received a lot of interest for their astonishing ability to produce high-fidelity images from text only. However, achieving one-shot ge…