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LLaVA-NeXT-Video is upgraded 🚀

In our LLaVA-Video blog released this April, we shared two key observations:

  • 🎬 AnyRes provides a shared and flexible representation between images and videos, and thus accommodates capability transfer between the two most common vision signals. Therefore, stronger image LMMs can naturally lead to stronger zero-shot video LMMs.
  • 🗂️ There is a lack of high-quality language-video data, including video instruction-following data, and thus naive tuning on existing public data at that time results in performance degradation. Therefore, there is an urgent need to build high-quality video captions and QA datasets to train LMMs for improved video performance.

Based on the insights, the new LLaVA-NeXT-Video in this release improves from two aspects:

  • 🎬 A stronger image LMMs (LLaVA-NeXT-32B-Qwen), which is built by initializing from Qwen-1.5 32B LLM. We further initialize our video training from this image checkpoint.
  • 🗂️ A new high-quality video dataset with 830k samples. It is combined with LLaVA-1.6 image training data, and applying the same image-video mixed training procedure leads to the new video model. The new model achieves the best open-source performance in several video benchmarks including Video-MME.

Resources

  • Model Card: LLaVA-NeXT-Video-32B-Qwen on Hugging Face
  • Inference Script: 
    bash scripts/video/demo/video_demo.sh lmms-lab/LLaVA-NeXT-Video-32B-Qwen qwen_1_5 32 2 average after grid True playground/demo/xU25MMA2N4aVtYay.mp4

Evaluation Results

Model NextQA-MC video-mme(overall) Egochema Perception Test (val)
w/o subs w subs
Proprietary
GPT-4o - 71.9 77.2 72.2 -
Gemini 1.5 Pro - 75.0 81.3 72.2 -
Open-Source
VideoLLaMA 2 (8x7B) 76.3* 47.9 50.3 53.3 51.2*
VILA-1.5-34B 67.89* 60.1 61.1 58.04* 54
LLaVA-NeXT-Video (Qwen-32B) 77.31 60.2 63.0 60.85 59.38

*Results are reproduced by lmms-eval. Please refer to the lmms-eval to reproduce the results.

Citations

@misc{zhang2024llavanextvideo,
  title={LLaVA-NeXT: A Strong Zero-shot Video Understanding Model},
  url={https://llava-vl.github.io/blog/2024-04-30-llava-next-video/},
  author={Zhang, Yuanhan and Li, Bo and Liu, haotian and Lee, Yong jae and Gui, Liangke and Fu, Di and Feng, Jiashi and Liu, Ziwei and Li, Chunyuan},
  month={April},
  year={2024}
}

@misc{li2024llavanext-interleave,
  title={LLaVA-NeXT: Tackling Multi-image, Video, and 3D in Large Multimodal Models},
  url={https://llava-vl.github.io/blog/2024-06-16-llava-next-interleave/},
  author={Li, Feng and Zhang, Renrui and Zhang, Hao and Zhang, Yuanhan and Li, Bo and Li, Wei and Ma, Zejun and Li, Chunyuan},
  month={June},
  year={2024}
}