arxiv preprint – Goldfish: Vision-Language Understanding of Arbitrarily Long Videos

In this episode, we discuss Goldfish: Vision-Language Understanding of Arbitrarily Long Videos by Kirolos Ataallah, Xiaoqian Shen, Eslam Abdelrahman, Essam Sleiman, Mingchen Zhuge, Jian Ding, Deyao Zhu, Jürgen Schmidhuber, Mohamed Elhoseiny. The paper introduces Goldfish, a methodology designed to efficiently comprehend videos of any length by employing a retrieval mechanism that selects top-k relevant video clips for processing. To evaluate its effectiveness, the authors present the TVQA-long benchmark aimed at long video understanding and demonstrate significant improvements over existing methods, achieving a 41.78% accuracy rate. Additionally, their MiniGPT4-Video model also excels in short video comprehension, outperforming current state-of-the-art methods on multiple benchmarks.