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Identity-Conditioned Latent Consistency Distillation for Face Synthesis

Paper recorded by Signals 4 on 2026-08-31 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-08-31 on arXiv · recorded by Signals 4 on 2026-09-01

Category: cs.CV · 计算机视觉 · first seen 2026-09-01

Abstract

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

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#200 most recent of 237 cs.CV papers we have recorded · ↑ newer: Multimodal Shared Latent Representation of Narration, Microscope and i · ↓ older: FaceSnap: Real-Time Personalized Lightstage Facial Performance Capture
Cite this page: Identity-Conditioned Latent Consistency Distillation for Face Synthesis: the #200 most recent of 237 cs.CV papers we have recorded (as of 2026-08-31). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/identity-conditioned-latent-consistency-distillation-for-face-synthesis.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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