mlsanityData to 14 Oct 2026

Edit Fidelity Field: Semantics-Aware Region Isolation for Training-Free Scene Text Editing

arXiv 2604.17500 ↗First posted 19 Apr 2026cs.CVcited by 0

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Abstract (arXiv)

Scene text editing (STE) has achieved remarkable progress in accurately rendering target text through diffusion-based methods. However, we identify a critical yet overlooked problem: edit spillover -- when editing a target text region, existing methods inadvertently modify non-target regions, particularly neighboring text. Through systematic evaluation on 50 real-world scenes across four categories, we reveal that state-of-the-art diffusion editing models exhibit a spillover rate of 94%, meaning nearly all non-target text regions are altered during editing. To address this, we propose the Edit Fidelity Field (EFF), a semantics-aware continuous field that controls per-pixel editing fidelity. Unlike binary masks, EFF leverages OCR-detected text regions to construct a four-zone field: Edit Core (fully editable), Transition Zone (smooth decay), Protected Zone (non-target text, explicitly locked), and Background (strictly preserved). EFF operates as a training-free, model-agnostic post-processing module applicable to any diffusion-based STE method. We further propose per-region spillover quantification, a novel evaluation protocol that measures edit leakage at each non-target text region individually. Experiments demonstrate that EFF reduces spillover rate from 94% to 25% while improving non-target region preservation by +91.4 dB PSNR.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 22 of its 28 references that are in the map. First posted on arXiv 19 Apr 2026.

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22 of 28 references.

References · 22

  1. 2022Scalable Diffusion Models with Transformerscited by 6,054
  2. 2021Blended Diffusion for Text-driven Editing of Natural Imagescited by 927
  3. 2022DiffEdit: Diffusion-based semantic image editing with mask guidancecited by 647
  4. 2020PP-OCR: A Practical Ultra Lightweight OCR Systemcited by 151
  5. 2024AnyText2: Visual Text Generation and Editing With Customizable Attributescited by 53
  6. 2020SwapText: Image Based Texts Transfer in Scenescited by 50
  7. 2019STEFANN: Scene Text Editor using Font Adaptive Neural Networkcited by 47
  8. 2024TextCtrl: Diffusion-based Scene Text Editing with Prior Guidance Controlcited by 45
  9. 2024FonTS: Text Rendering with Typography and Style Controlscited by 40
  10. 2024GlyphDraw2: Automatic Generation of Complex Glyph Posters with Diffusion Models and Large Language Modelscited by 29
  11. 2024DreamText: High Fidelity Scene Text Synthesiscited by 18
  12. 2026TextPecker: Rewarding Structural Anomaly Quantification for Enhancing Visual Text Renderingcited by 15
10 more
  1. 2025Recognition-Synergistic Scene Text Editingcited by 12
  2. 2025GlyphMastero: A Glyph Encoder for High-Fidelity Scene Text Editingcited by 11
  3. 2025EditID: Training-Free Editable ID Customization for Text-to-Image Generationcited by 8
  4. 2025EditIDv2: Editable ID Customization with Data-Lubricated ID Feature Integration for Text-to-Image Generationcited by 8
  5. 2026Dual-Channel Attention Guidance for Training-Free Image Editing Control in Diffusion Transformerscited by 6
  6. 2026GlyphPrinter: Region-Grouped Direct Preference Optimization for Glyph-Accurate Visual Text Renderingcited by 6
  7. 2024TextMaster: A Unified Framework for Realistic Text Editing via Glyph-Style Dual-Controlcited by 5
  8. 2026GlyphBanana: Advancing Precise Text Rendering Through Agentic Workflowscited by 4
  9. 2026FlexID: Training-Free Flexible Identity Injection via Intent-Aware Modulation for Text-to-Image Generationcited by 3
  10. 2026Edit Spillover as a Probe: Do Image Editing Models Implicitly Understand World Relations?cited by 1

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