arXiv (All)
open access
PixelART: Image-to-Layer Decomposition without Latents or Text-to-Image Pretraining
Image-to-layer decomposition converts a flattened image into editable RGBA layers, enabling element-level editing in design workflows. Existing diffusion-based systems typically adapt large pretrained text-to-image (T2I) models and introduce RGBA autoencoders or variable-layer architectural modules.
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
- Advances in Diffusion-Based Generative Compression#1062833
- Constrained Edit Fields for Training-Free Flow Editing#1118808
- VIEScore2: Unified Image Evaluation with Spatially Grounded Explanations#1155929
- RAPID: A Real-Time Defense Against Unauthorized Model Distillation for Text-to-Image Services#1109845
- RAPID: A Real-Time Defense Against Unauthorized Model Distillation for Text-to-Image Services#919281
Record · ID 1037472
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