LLaVA-OneVision: Easy Visual Task Transfer

Bo Li, Zhang Yuanhan, Dong Guo, Renrui Zhang, Feng Li, Hao Zhang, kcz, Yanwei Li, Ziwei Liu, Chunyuan Li

LLaVA-OneVision: Easy Visual Task Transfer: 61 upvotes on Hugging Face Daily Papers, #2 of 12 papers on 2024-08-07. Day-by-day upvote history.

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.

Paper page on Hugging Face · arXiv

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