SOURCE-LINKED INTELLIGENCE
Identity-Conditioned Latent Consistency Distillation for Face Synthesis
Diffusion models have achieved strong results in high-fidelity image synthesis, but their iterative sampling process makes large-scale generation computationally expensive. This limitation is especially relevant when generating synthetic face datasets for face recognition, where a large number of subjects with many samples in different poses, expressions, ages, etc., are required. In this work, we show that identity-conditioned face synthesis can be performed at a substantially lower computational cost by a latent Consistency Model with few iterations, without compromising image quality. For t
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-31T16:32:40.000Z
First collected: 2026-09-21T06:41:57.136Z. This is not the publication date.