Semantic Role Aware Correlation Transformer for Text to Video Retrieval

• URL: http://arxiv.org/abs/2206.12849v1
• Date: Sun, 26 Jun 2022 11:28:03 GMT
• Title: Semantic Role Aware Correlation Transformer for Text to Video Retrieval
• Authors: Burak Satar, Hongyuan Zhu, Xavier Bresson, Joo Hwee Lim
• Abstract summary: This paper proposes a novel transformer that explicitly disentangles the text and video into semantic roles of objects, spatial contexts and temporal contexts. Preliminary results on popular YouCook2 indicate that our approach surpasses a current state-of-the-art method, with a high margin in all metrics.
• Score: 23.183653281610866
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: With the emergence of social media, voluminous video clips are uploaded every day, and retrieving the most relevant visual content with a language query becomes critical. Most approaches aim to learn a joint embedding space for plain textual and visual contents without adequately exploiting their intra-modality structures and inter-modality correlations. This paper proposes a novel transformer that explicitly disentangles the text and video into semantic roles of objects, spatial contexts and temporal contexts with an attention scheme to learn the intra- and inter-role correlations among the three roles to discover discriminative features for matching at different levels. The preliminary results on popular YouCook2 indicate that our approach surpasses a current state-of-the-art method, with a high margin in all metrics. It also overpasses two SOTA methods in terms of two metrics.

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