Summary of Videoprism: a Foundational Visual Encoder For Video Understanding, by Long Zhao et al.
VideoPrism: A Foundational Visual Encoder for Video Understanding
by Long Zhao, Nitesh B. Gundavarapu, Liangzhe Yuan, Hao Zhou, Shen Yan, Jennifer J. Sun, Luke Friedman, Rui Qian, Tobias Weyand, Yue Zhao, Rachel Hornung, Florian Schroff, Ming-Hsuan Yang, David A. Ross, Huisheng Wang, Hartwig Adam, Mikhail Sirotenko, Ting Liu, Boqing Gong
First submitted to arxiv on: 20 Feb 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary VideoPrism is a novel video encoder that can tackle various video understanding tasks using a single frozen model. Pretrained on a large corpus containing high-quality video-caption pairs and noisy parallel text, VideoPrism leverages the strengths of both modalities to improve its performance. The encoder achieves state-of-the-art results on 31 out of 33 video understanding benchmarks across four broad categories. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary VideoPrism is a special kind of computer program that can understand videos in many different ways. It was trained using lots of information about videos and what they say. This helps the program get really good at recognizing things in videos, answering questions about them, and even helping scientists make new discoveries! The creators tested it on many challenges and it did better than any other program on most of them. |
Keywords
» Artificial intelligence » Encoder
