A CLIP-Enhanced Method for Video-Language Understanding

This technical report summarizes our method for the Video-And-Language Understanding Evaluation (VALUE) challenge (https://value-benchmark.github.io/challenge\_2021.html). We propose a CLIP-Enhanced method to incorporate the image-text pretrained knowledge into downstream video-text tasks. Combined...

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Bibliographic Details
Main Authors Li, Guohao, He, Feng, Feng, Zhifan
Format Journal Article
LanguageEnglish
Published 13.10.2021
Subjects
Computer Science - Computation and Language
Computer Science - Computer Vision and Pattern Recognition
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Summary:This technical report summarizes our method for the Video-And-Language Understanding Evaluation (VALUE) challenge (https://value-benchmark.github.io/challenge\_2021.html). We propose a CLIP-Enhanced method to incorporate the image-text pretrained knowledge into downstream video-text tasks. Combined with several other improved designs, our method outperforms the state-of-the-art by $2.4\%$ ($57.58$ to $60.00$) Meta-Ave score on VALUE benchmark.
DOI:10.48550/arxiv.2110.07137