MAST: Mask-Guided Attention Control for Training-Free Regional-Multi Style Transfer

arXiv:2604.12281 · cs.CV, cs.AI · Submitted 2026-04-14 · Read on arXiv

cs.CV, cs.AI

Submitted: 2026-04-14

Updated: 2026-09-06

Comments: 23 pages, 17 figures, 13 tables

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Fidelity — 21× in this paper · explained in 2 episodes
• Consistency — 17× in this paper · explained in 3 episodes
• Diffusion Model — 13× in this paper · explained in 8 episodes
• Diffusion Models — 12× in this paper · explained in 6 episodes
• Guided attention — 11× in this paper · explained in 2 episodes
• Discrepancy-aware Detail Injection — 6× in this paper
• Logit-level Attention Mass Allocation — 6× in this paper
• Sharpness-aware Temperature Scaling — 6× in this paper
• Alignment — 5× in this paper · explained in 1 episode
• Attention Mechanism — 5× in this paper · explained in 3 episodes
• Transformer — 5× in this paper · explained in 2 episodes
• Ablation — 4× in this paper · explained in 1 episode
• Latent Diffusion Model — 4× in this paper · explained in 2 episodes
• Latent Diffusion Models — 4× in this paper · explained in 2 episodes
• Robustness — 4× in this paper · explained in 5 episodes
• Ablation study — 3× in this paper · explained in 1 episode
• Core — 3× in this paper · explained in 2 episodes
• Layout-preserving Query Anchoring — 3× in this paper
• Training-Free Framework — 3× in this paper · explained in 2 episodes
• Aggregation — 2× in this paper · explained in 1 episode
• Adaptability — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Calibration — 1× in this paper · explained in 7 episodes
• Contrastive Learning — 1× in this paper · explained in 5 episodes
• Diffusion Process — 1× in this paper · explained in 2 episodes
• Domain Adaptation — 1× in this paper · explained in 5 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Latent Diffusion Models (LDMs) — 1× in this paper · explained in 2 episodes
• Latent Representation — 1× in this paper · explained in 2 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Mean Absolute Difference — 1× in this paper
• Transformer Architecture — 1× in this paper · explained in 2 episodes
• U-net architecture — 1× in this paper · explained in 3 episodes

Sources

• ConsisLoRA: Enhancing Content and Style Consistency for LoRA-based Style Transfer
• Style Transfer with Diffusion Models for Synthetic-to-Real Domain Adaptation
• A Learned Representation For Artistic Style
• AttenST: A Training-Free Attention-Driven Style Transfer Framework with Pre-Trained Diffusion Models
• Training-free Content Injection using h-space in Diffusion Models
• Microsoft COCO: Common Objects in Context
• Denoising Diffusion Implicit Models
• Softmax is not Enough (for Sharp Size Generalisation)
• CDST: Color Disentangled Style Transfer for Universal Style Reference Customization

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