Mini-Gemini: Mining the Potential of Multi-Modality Vision Language Models(arxiv.org)
arxiv.org
Mini-Gemini: Mining the Potential of Multi-Modality Vision Language Models
https://arxiv.org/abs/2403.18814
9 comments
Excite to see how this does on open compass!
WTF is a "Multi-modality Vision Language Model"? Does it mean:
- a program where you give it a text description, and it outputs a picture
- a program where you give it a picture, and it outputs a text description
- both of the above
- something else
?
- a program where you give it a text description, and it outputs a picture
- a program where you give it a picture, and it outputs a text description
- both of the above
- something else
?
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The paper introduces Mini-Gemini, a framework aimed at enhancing Vision Language Models (VLMs) to close the performance gap with advanced models like GPT-4 and Gemini. It focuses on improving visual tokens resolution, creating high-quality datasets for better image comprehension, and expanding VLMs' operational scope. Mini-Gemini supports a range of large language models and has shown superior performance in zero-shot benchmarks. The code and models are publicly available.
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Project website - https://mini-gemini.github.io/
Code and Models - https://github.com/dvlab-research/MiniGemini
Mini-Gemini is a bit of a confusing name.
Reminds me of how DALL·E Mini came out three years ago and eventually had to rename itself to Craiyon https://github.com/borisdayma/dalle-mini
Reminds me of how DALL·E Mini came out three years ago and eventually had to rename itself to Craiyon https://github.com/borisdayma/dalle-mini
Is this based on LLaVA 1.6? Not to be too lazy, but maybe someone could link to a comparison with that, if there is one?