all AI news
Text-IF: Leveraging Semantic Text Guidance for Degradation-Aware and Interactive Image Fusion
March 26, 2024, 4:47 a.m. | Xunpeng Yi, Han Xu, Hao Zhang, Linfeng Tang, Jiayi Ma
cs.CV updates on arXiv.org arxiv.org
Abstract: Image fusion aims to combine information from different source images to create a comprehensively representative image. Existing fusion methods are typically helpless in dealing with degradations in low-quality source images and non-interactive to multiple subjective and objective needs. To solve them, we introduce a novel approach that leverages semantic text guidance image fusion model for degradation-aware and interactive image fusion task, termed as Text-IF. It innovatively extends the classical image fusion to the text guided …
arxiv cs.cv fusion guidance image interactive semantic text type
More from arxiv.org / cs.CV updates on arXiv.org
Jobs in AI, ML, Big Data
Data Architect
@ University of Texas at Austin | Austin, TX
Data ETL Engineer
@ University of Texas at Austin | Austin, TX
Lead GNSS Data Scientist
@ Lurra Systems | Melbourne
Senior Machine Learning Engineer (MLOps)
@ Promaton | Remote, Europe
Reporting & Data Analytics Lead (Sizewell C)
@ EDF | London, GB
Data Analyst
@ Notable | San Mateo, CA