research-article

Fine-Grained Text-to-Video Temporal Grounding from Coarse Boundary

Authors:

Jianxin LiaoAuthors Info & Claims

ACM Transactions on Multimedia Computing, Communications and Applications, Volume 19, Issue 5

Article No.: 157, Pages 1 - 21

https://doi.org/10.1145/3579825

Published: 16 March 2023 Publication History

Abstract

Text-to-video temporal grounding aims to locate a target video moment that semantically corresponds to the given sentence query in an untrimmed video. In this task, fully supervised works require text descriptions for each event along with its temporal segment coordinate for training, which is labor-consuming. Existing weakly supervised works require only video-sentence pairs but cannot achieve satisfactory performance. However, many available annotations in the form of coarse temporal boundaries for sentences are ignored and unexploited. These coarse boundaries are common in streaming media platform and can be collected in a mechanical manner. We propose a novel approach to perform fine-grained text-to-video temporal grounding from these coarse boundaries. We take dense video captioning as base task and leverage the trained captioning model to identify the relevance of each video frame to the sentence query according to the frame participation in event captioning. To quantify the frame participation in event captioning, we propose event activation sequence, a simple method that highlights the temporal regions which have high correlations to the text modality in videos. Experiments on modified ActivityNet Captions and a use case demonstrate the promising fine-grained performance of our approach.

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Cited By

Yin SZhao SWang HXu TChen E(2024)Exploiting Instance-level Relationships in Weakly Supervised Text-to-Video RetrievalACM Transactions on Multimedia Computing, Communications, and Applications10.1145/366357120:10(1-21)Online publication date: 12-Sep-2024
https://dl.acm.org/doi/10.1145/3663571

Index Terms

Fine-Grained Text-to-Video Temporal Grounding from Coarse Boundary
1. Information systems
  1. Information retrieval
    1. Specialized information retrieval
      1. Multimedia and multimodal retrieval
        Video search

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cover image ACM Transactions on Multimedia Computing, Communications, and Applications

ACM Transactions on Multimedia Computing, Communications, and Applications Volume 19, Issue 5

September 2023

262 pages

ISSN:1551-6857

EISSN:1551-6865

DOI:10.1145/3585398

Editor:
Abdulmotaleb El Saddik
Mohamed Bin Zayed University of Artificial Intelligence, UAE and University of Ottawa, Canada

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Publication History

Published: 16 March 2023

Online AM: 12 January 2023

Accepted: 03 January 2023

Revised: 23 October 2022

Received: 20 June 2022

Published in TOMM Volume 19, Issue 5

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National Natural Science Foundation of China
Ministry of Education and China Mobile Joint Fund
Beijing University of Posts and Telecommunications-China Mobile Research Institute Joint Innovation Center

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Yin SZhao SWang HXu TChen E(2024)Exploiting Instance-level Relationships in Weakly Supervised Text-to-Video RetrievalACM Transactions on Multimedia Computing, Communications, and Applications10.1145/366357120:10(1-21)Online publication date: 12-Sep-2024
https://dl.acm.org/doi/10.1145/3663571

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