A Straightforward Framework For Video Retrieval Using CLIP

• URL: http://arxiv.org/abs/2102.12443v2
• Date: Fri, 26 Feb 2021 17:55:07 GMT
• Title: A Straightforward Framework For Video Retrieval Using CLIP
• Authors: Jes\'us Andr\'es Portillo-Quintero, Jos\'e Carlos Ortiz-Bayliss, Hugo Terashima-Mar\'in
• Abstract summary: Video Retrieval is a challenging task where a text query is matched to a video or vice versa. Most of the existing approaches for addressing such a problem rely on annotations made by the users. In this work, we explore the application of the language-image model, CLIP, to obtain video representations without the need for said annotations.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Video Retrieval is a challenging task where a text query is matched to a video or vice versa. Most of the existing approaches for addressing such a problem rely on annotations made by the users. Although simple, this approach is not always feasible in practice. In this work, we explore the application of the language-image model, CLIP, to obtain video representations without the need for said annotations. This model was explicitly trained to learn a common space where images and text can be compared. Using various techniques described in this document, we extended its application to videos, obtaining state-of-the-art results on the MSR-VTT and MSVD benchmarks.

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