ReGain: Restoring Subject Fidelity in Personalization on Synthetic Images

arXiv:2609.38680 · cs.CV, cs.AI, cs.LG, eess.IV · Submitted 2026-09-30 · Read on arXiv

cs.CV, cs.AI, cs.LG, eess.IV

Submitted: 2026-09-30

Updated: 2026-09-30

Terminology

• Fidelity — 24× in this paper · explained in 2 episodes
• Fine-Tuning — 19× in this paper · explained in 5 episodes
• Diffusion Model — 18× in this paper · explained in 8 episodes
• Diffusion Models — 14× in this paper · explained in 6 episodes
• Calibration — 10× in this paper · explained in 7 episodes
• Personalization — 10× in this paper · explained in 2 episodes
• Transformer — 6× in this paper · explained in 2 episodes
• Computer Vision and Pattern Recognition — 4× in this paper
• Generative Model — 4× in this paper · explained in 2 episodes
• Generative Models — 4× in this paper · explained in 2 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Cosine Similarity — 3× in this paper · explained in 3 episodes
• Embeddings — 3× in this paper · explained in 2 episodes
• Trace — 3× in this paper · explained in 2 episodes
• Generative AI — 2× in this paper · explained in 2 episodes
• International Conference on Computer Vision — 2× in this paper
• Latent Diffusion Model — 2× in this paper · explained in 2 episodes
• Latent Diffusion Models — 2× in this paper · explained in 2 episodes
• Steering — 2× in this paper · explained in 2 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Consistency — 1× in this paper · explained in 3 episodes
• Data Provenance — 1× in this paper · explained in 2 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• In-Context Learning — 1× in this paper · explained in 4 episodes
• Joint Attention — 1× in this paper · explained in 2 episodes
• LoRA Adapters — 1× in this paper · explained in 3 episodes
• Provenance — 1× in this paper · explained in 3 episodes
• Rectified Flow — 1× in this paper · explained in 3 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Transformer Models — 1× in this paper · explained in 2 episodes

Sources

• Classifier-Free Diffusion Guidance
• Guidance in the Frequency Domain Enables High-Fidelity Sampling at Low CFG Scales
• IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models

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