3 papers
cs.CR2026
From Easy to Hard++: Promoting Differentially Private Image Synthesis Through Spatial-Frequency Curriculum
Chen Gong, Kecen Li, Zinan Lin +1
To improve the quality of Differentially private (DP) synthetic images, most studies have focused on improving the core optimization techniques (e.g., DP-SGD). Recently, we have wi…
cs.CV2025
Synthesize Privacy-Preserving High-Resolution Images via Private Textual Intermediaries
Haoxiang Wang, Zinan Lin, Da Yu +1
Generating high fidelity, differentially private (DP) synthetic images offers a promising route to share and analyze sensitive visual data without compromising individual privacy.…
cs.CR2025
DPImageBench: A Unified Benchmark for Differentially Private Image Synthesis
Chen Gong, Kecen Li, Zinan Lin +1
Differentially private (DP) image synthesis aims to generate artificial images that retain the properties of sensitive images while protecting the privacy of individual images with…