all AI news
In-Context Translation: Towards Unifying Image Recognition, Processing, and Generation
April 16, 2024, 4:47 a.m. | Han Xue, Qianru Sun, Li Song, Wenjun Zhang, Zhiwu Huang
cs.CV updates on arXiv.org arxiv.org
Abstract: We propose In-Context Translation (ICT), a general learning framework to unify visual recognition (e.g., semantic segmentation), low-level image processing (e.g., denoising), and conditional image generation (e.g., edge-to-image synthesis). Thanks to unification, ICT significantly reduces the inherent inductive bias that comes with designing models for specific tasks, and it maximizes mutual enhancement across similar tasks. However, the unification across a large number of tasks is non-trivial due to various data formats and training pipelines. To this …
abstract arxiv bias context cs.cv denoising designing edge framework general ict image image generation image processing image recognition inductive low processing recognition segmentation semantic specific tasks synthesis tasks translation type unification visual
More from arxiv.org / cs.CV updates on arXiv.org
Jobs in AI, ML, Big Data
Software Engineer for AI Training Data (School Specific)
@ G2i Inc | Remote
Software Engineer for AI Training Data (Python)
@ G2i Inc | Remote
Software Engineer for AI Training Data (Tier 2)
@ G2i Inc | Remote
Data Engineer
@ Lemon.io | Remote: Europe, LATAM, Canada, UK, Asia, Oceania
Artificial Intelligence – Bioinformatic Expert
@ University of Texas Medical Branch | Galveston, TX
Lead Developer (AI)
@ Cere Network | San Francisco, US