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A new video captioning framework named Wolf has been introduced, leveraging a mixture-of-experts approach to enhance accuracy in video captioning. Developed by a team including B. Li, L. Zhu, R. Tian, and S. Tan from NVIDIA, Wolf utilizes multiple vision-language models (VLMs) to generate captions. The framework has demonstrated superior performance compared to existing models like GPT-4V and Gemini-Pro-1.5, particularly in various contexts such as general scenes, autonomous driving, and robotics. The release of Wolf is seen as a significant advancement in video captioning technology, which is increasingly vital for the development of autonomous vehicles and robotics.
Video captioning is nowadays a critical tool to fuel data flywheels for AV and robot development. We have just released Wolf: a novel video captioning framework achieving SOTA in a number of settings: Paper: https://t.co/eShRDP9Rfz Related challenge: https://t.co/DhOvGQzv6R https://t.co/d68ARmL1yU
🚀 Introducing 𝐖𝐨𝐥𝐟 🐺: a mixture-of-experts video captioning framework that outperforms GPT-4V and Gemini-Pro-1.5 in general scenes 🖼️, autonomous driving 🚗, and robotics videos 🤖. 👑: https://t.co/cOEfUvRL0m https://t.co/Fc0FIZN1oB
🚨Wolf: Captioning Everything with a World Summarization Framework 🌟𝐏𝐫𝐨𝐣: https://t.co/9WW2sUZV2b 🚀𝐀𝐛𝐬: https://t.co/7DnupK5KVQ propose Wolf, a WOrLd summarization Framework for accurate video captioning. https://t.co/TBgfNZD7we