Summary of Olympus: a Universal Task Router For Computer Vision Tasks, by Yuanze Lin et al.
Olympus: A Universal Task Router for Computer Vision Tasks
by Yuanze Lin, Yunsheng Li, Dongdong Chen, Weijian Xu, Ronald Clark, Philip H. S. Torr
First submitted to arxiv on: 12 Dec 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); Computation and Language (cs.CL)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper introduces Olympus, a novel approach that transforms Multimodal Large Language Models (MLLMs) into a unified framework capable of handling various computer vision tasks. By utilizing a controller MLLM and delegating tasks to dedicated modules, Olympus enables complex workflows through chained actions without requiring heavy generative model training. The approach integrates seamlessly with existing MLLMs, expanding their capabilities while maintaining comparable performance. Experimental results demonstrate Olympus’ effectiveness in solving diverse computer vision tasks, achieving an average routing accuracy of 94.75% and precision of 91.82%. This new universal task router showcases its potential to revolutionize the field. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Olympus is a new way to use big language models for computer vision tasks. It takes these models and makes them work together to do many different jobs, like recognizing objects in images or understanding video sequences. Olympus is special because it doesn’t need to be trained on all of these tasks separately – it can learn how to route tasks to the right modules without needing a lot of extra training data. This means it can quickly adapt to new tasks and work efficiently with existing models. The results show that Olympus is very accurate, achieving 94.75% accuracy across many different tasks. |
Keywords
» Artificial intelligence » Generative model » Precision
