arXiv (All)
open access
RefDiT: Local Attribute Guidance in Reference-Based Image Generation
Personalization models generate new images guided by a few subject references, while style transfer methods aim to produce images aligned with a global style derived from a reference image. Recent approaches perform well when the reference image contains a single object, effectively capturing a glob
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
- Amplify What You Gaze At: Target Saliency Boosting in Text-to-Image Generation#1105292
- TASTE: A Designer-Annotated Multi-Dimensional Preference Dataset for AI-Generated Graphic Design#1049842
- Long-Text-to-Image Generation via Compositional Prompt Decomposition#120569
- InsightTok: Improving Text and Face Fidelity in Discrete Tokenization for Autoregressive Image Generation#196161
- GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation#1034753
Record · ID 971937
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