Wolf: Captioning Everything with a World Summarization Framework
<|reference_start|>Wolf: Captioning Everything with a World Summarization Framework: We propose Wolf, a WOrLd summarization Framework for accurate video captioning. Wolf is an automated captioning framework that adopts a mixture-of-experts approach, leveraging complementary strengths of Vision Language Models (VLMs). By utilizing both image and video models, our framework captures different levels of information and summarizes them efficiently. Our approach can be applied to enhance video understanding, auto-labeling, and captioning. To evaluate caption quality, we introduce CapScore, an LLM-based metric to assess the similarity and quality of generated captions compared to the ground truth captions. We further build four human-annotated datasets in three domains: autonomous driving, general scenes, and robotics, to facilitate comprehensive comparisons. We show that Wolf achieves superior captioning performance compared to state-of-the-art approaches from the research community (VILA1.5, CogAgent) and commercial solutions (Gemini-Pro-1.5, GPT-4V). For instance, in comparison with GPT-4V, Wolf improves CapScore both quality-wise by 55.6% and similarity-wise by 77.4% on challenging driving videos. Finally, we establish a benchmark for video captioning and introduce a leaderboard, aiming to accelerate advancements in video understanding, captioning, and data alignment. Leaderboard: https://wolfv0.github.io/leaderboard.html.<|reference_end|>
@article{li2024wolf:,
    title={Wolf: Captioning Everything with a World Summarization Framework},
    author={Boyi Li and Ligeng Zhu and Ran Tian and Shuhan Tan and Yuxiao Chen and
  Yao Lu and Yin Cui and Sushant Veer and Max Ehrlich and Jonah Philion and
  Xinshuo Weng and Fuzhao Xue and Andrew Tao and Ming-Yu Liu and Sanja Fidler
  and Boris Ivanovic and Trevor Darrell and Jitendra Malik and Song Han and
  Marco Pavone},
    journal={arXiv preprint arXiv:2407.18908},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.18908},
    primaryClass={cs.LG cs.CL cs.CV}
}