arXiv (All)
open access
Weak Segmentation-Guided GAN for~Realistic Color Edition
Editing the color of images in a realistic way finds many applications such as changing the perception of an image, data augmentation or film post processing. The design of an automatic tool is a complex and long addressed challenge. In particular, two properties are difficult to meet altogether: ge
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
- Learning Representations to Guide Pixel Diffusion Transformers#1297330
- ProGAN-Based Synthetic Image Generation for Industrial Visual Inspection of Metallic Parts#1327877
- Adversarial Training for Pixel Diffusion#1142465
- ROMS-IMLE: A Minimalist Approach to Competitive Single-Step Generative Modelling#926127
- Dosimetric Validation of Scans Generated by GAN From Pre-therapeutic MRI in Stereotactic Cerebral Radiotherapy#1126754
Record · ID 1328210
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