Refinement Is Inherently Editable: Training-Free Prompt-to-Prompt Image Editing with Generative Refinement Network

arXiv:2609.20633 · cs.CV · Submitted 2026-09-17 · Read on arXiv

cs.CV

Submitted: 2026-09-17

Updated: 2026-09-25

Terminology

• Alignment — 12× in this paper · explained in 1 episode
• Conference on Computer Vision and Pattern Recognition — 8× in this paper
• Transformer — 7× in this paper · explained in 2 episodes
• Generative Refinement Network — 5× in this paper
• Quantization — 5× in this paper · explained in 12 episodes
• Ablation — 4× in this paper · explained in 1 episode
• Fidelity — 4× in this paper · explained in 2 episodes
• Semantic Alignment — 4× in this paper · explained in 3 episodes
• Consistency — 3× in this paper · explained in 3 episodes
• Decode — 3× in this paper · explained in 2 episodes
• Diffusion Model — 3× in this paper · explained in 8 episodes
• Diffusion Models — 3× in this paper · explained in 6 episodes
• Hierarchical Binary Quantization — 3× in this paper
• Training-Free Framework — 3× in this paper · explained in 2 episodes
• Accuracy — 2× in this paper · explained in 1 episode
• Benchmark — 2× in this paper · explained in 2 episodes
• Core — 2× in this paper · explained in 2 episodes
• Generative Model — 2× in this paper · explained in 2 episodes
• Generative Models — 2× in this paper · explained in 2 episodes
• Latent Diffusion Model — 2× in this paper · explained in 2 episodes
• Latent Diffusion Models — 2× in this paper · explained in 2 episodes
• Aggregation — 1× in this paper · explained in 1 episode
• CVF International Conference on Computer Vision — 1× in this paper
• Distillation — 1× in this paper · explained in 2 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Flow Matching — 1× in this paper · explained in 8 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• M EAN S QUARED E RROR — 1× in this paper
• Optimal Transport — 1× in this paper · explained in 5 episodes
• Rectified Flow — 1× in this paper · explained in 3 episodes
• World Model — 1× in this paper · explained in 7 episodes

Sources

• VideoPoet: A Large Language Model for Zero-Shot Video Generation
• FLUX.1 Kontext: Flow Matching for In-Context Image Generation and Editing in Latent Space
• ChordEdit: One-Step Low-Energy Transport for Image Editing
• Grounded SAM: Assembling Open-World Models for Diverse Visual Tasks
• Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation
• Scaling Autoregressive Models for Content-Rich Text-to-Image Generation

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