2 citations · 2 across the 5 of their papers we have counts for
Showing 2024Show all
3 papers · 1 filter
cs.CV2024
VersusDebias: Universal Zero-Shot Debiasing for Text-to-Image Models via SLM-Based Prompt Engineering and Generative Adversary
Hanjun Luo, Ziye Deng, Haoyu Huang +3
With the rapid development of Text-to-Image (T2I) models, biases in human image generation against demographic social groups become a significant concern, impacting fairness and et…
cs.CV2024★ 2 cited
BIGbench: A Unified Benchmark for Evaluating Multi-dimensional Social Biases in Text-to-Image Models
Hanjun Luo, Haoyu Huang, Ziye Deng +6
Text-to-Image (T2I) generative models are becoming increasingly crucial due to their ability to generate high-quality images, but also raise concerns about social biases, particula…
cs.CV2024
FAIntbench: A Holistic and Precise Benchmark for Bias Evaluation in Text-to-Image Models
Hanjun Luo, Ziye Deng, Ruizhe Chen +1
The rapid development and reduced barriers to entry for Text-to-Image (T2I) models have raised concerns about the biases in their outputs, but existing research lacks a holistic de…