arXiv (All)
open access
ODDR: One-Step Deshadow Diffusion via Reward Guidance
Recent advances in deep learning for shadow removal have significantly enhanced image quality and realism. However, most approaches rely on real-world paired datasets, which are costly to collect and often limited in scene diversity, leading to limited generalization. To address these limitations, w
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
- After a Decade: Bringing Shadow Removal into the Real World with Agentic Training Data#1143208
- Domain shift-robust object detection with GenAI image editing#924196
- Domain shift-robust object detection with GenAI image editing#919965
- GenNVS: Geometry-enhanced Novel View Synthesis via Disentangled 3D Prior#1131665
- SGPDFuse: Semantically-Guided Physics-Disentanglement General Multi-Modal Image Fusion#794032
Record · ID 1156563
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