arXiv (All)
open access
Real In, Real Out: What If We Only Use Real Data for Scene Text Editing?
Aiming to modify textual content while preserving the original style, Scene Text Editing (STE) has significant practical value in many applications. STE typically requires paired images before and after editing for training. However, recent approaches rely heavily on synthetic paired data and comple
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- BLANC: Adaptive Temporal Scheduling for Sign Language Production#1388675
- Motion Concept Unlearning in Video Diffusion Models#1132033
- Controllable Exaggeration for Generative Motion Models via Training-Time Adaptation and Inference-Time Guidance#1249740
- LARE: Low-Attention Region Encoding for Text-Image Retrieval#1048706
- Transformation Laws in Neural Representations: Structure, Realisability, and Construction#1011884
Record · ID 1403388
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive