arXiv:2408.03326cs.CV
LLaVA-OneVision: Easy Visual Task Transfer
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Abstract
We present LLaVA-OneVision, a family of open large multimodal models (LMMs) developed by consolidating our insights into data, models, and visual representations in the LLaVA-NeXT blog series. Our experimental results demonstrate that LLaVA-OneVision is the first single model that can simultaneously push the performance boundaries of open LMMs in three important computer vision scenarios: single-image, multi-image, and video scenarios. Importantly, the design of LLaVA-OneVision allows strong transfer learning across different modalities/scenarios, yielding new emerging capabilities. In particular, strong video understanding and cross-scenario capabilities are demonstrated through task transfer from images to videos.
The assessments of visual capability really need to be more robust. They are still using datasets like VQAv2, which while providing some insight, have many issues. There are many newer datasets that serve as much more robust tests and that are less prone to being affected by…
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