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Cross-Modal Video Moment Retrieval with Spatial and Language-Temporal Attention

Authors:

Junsong YuanAuthors Info & Claims

ICMR '19: Proceedings of the 2019 on International Conference on Multimedia Retrieval

Pages 217 - 225

https://doi.org/10.1145/3323873.3325019

Published: 05 June 2019 Publication History

Abstract

Given an untrimmed video and a description query, temporal moment retrieval aims to localize the temporal segment within the video that best describes the textual query. Existing studies predominantly employ coarse frame-level features as the visual representation, obfuscating the specific details which may provide critical cues for localizing the desired moment. We propose a SLTA (short for "Spatial and Language-Temporal Attention") method to address the detail missing issue. Specifically, the SLTA method takes advantage of object-level local features and attends to the most relevant local features (e.g., the local features "girl", "cup") by spatial attention. Then we encode the sequence of local features on consecutive frames to capture the interaction information among these objects (e.g., the interaction "pour" involving these two objects). Meanwhile, a language-temporal attention is utilized to emphasize the keywords based on moment context information. Therefore, our proposed two attention sub-networks can recognize the most relevant objects and interactions in the video, and simultaneously highlight the keywords in the query. Extensive experiments on TACOS, Charades-STA and DiDeMo datasets demonstrate the effectiveness of our model as compared to state-of-the-art methods.

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Cited By

Liu NSun XYu HYao FXu GFu K(2024)M2DCapsN: Multimodal, Multichannel, and Dual-Step Capsule Network for Natural Language Moment LocalizationIEEE Transactions on Neural Networks and Learning Systems10.1109/TNNLS.2023.326192735:8(11448-11462)Online publication date: Aug-2024
https://doi.org/10.1109/TNNLS.2023.3261927
Zeng YHan NPan KJin Q(2024)Temporally Language Grounding With Multi-Modal Multi-Prompt TuningIEEE Transactions on Multimedia10.1109/TMM.2023.331028226(3366-3377)Online publication date: 2024
https://doi.org/10.1109/TMM.2023.3310282
Wang RFeng JZhang FLuo XLuo Y(2024)Modality-Aware Heterogeneous Graph for Joint Video Moment Retrieval and Highlight DetectionIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2024.338902434:9(8896-8911)Online publication date: Sep-2024
https://doi.org/10.1109/TCSVT.2024.3389024
Show More Cited By

Index Terms

Cross-Modal Video Moment Retrieval with Spatial and Language-Temporal Attention
1. Information systems
  1. Information retrieval
    1. Specialized information retrieval
      1. Multimedia and multimodal retrieval
        Video search

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Published In

cover image ACM Conferences

ICMR '19: Proceedings of the 2019 on International Conference on Multimedia Retrieval

June 2019

427 pages

ISBN:9781450367653

DOI:10.1145/3323873

General Chairs:
Abdulmotaleb El Saddik
University of Ottawa, Canada
,
Alberto Del Bimbo
University of Florence, Italy
,
Zhongfei Zhang
Binghamton University, State University of New York, USA
,
Program Chairs:
Alexander Hauptmann
Carnegie Mellon University, USA
,
K. Selcuk Candan
Arizona State University, USA
,
Marco Bertini
University of Florence, Italy
,
Lexing Xie
Australia National University, Australia
,
Xiao-Yong Wei
Sichuan University, China

Copyright © 2019 ACM.

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SIGMM: ACM Special Interest Group on Multimedia

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Association for Computing Machinery

New York, NY, United States

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Published: 05 June 2019

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Natural Science Foundation of Hunan Province
National Natural Science Foundation of China

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ICMR '19

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SIGMM

ICMR '19: International Conference on Multimedia Retrieval

June 10 - 13, 2019

Ottawa ON, Canada

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Overall Acceptance Rate 254 of 830 submissions, 31%

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Cited By

Liu NSun XYu HYao FXu GFu K(2024)M2DCapsN: Multimodal, Multichannel, and Dual-Step Capsule Network for Natural Language Moment LocalizationIEEE Transactions on Neural Networks and Learning Systems10.1109/TNNLS.2023.326192735:8(11448-11462)Online publication date: Aug-2024
https://doi.org/10.1109/TNNLS.2023.3261927
Zeng YHan NPan KJin Q(2024)Temporally Language Grounding With Multi-Modal Multi-Prompt TuningIEEE Transactions on Multimedia10.1109/TMM.2023.331028226(3366-3377)Online publication date: 2024
https://doi.org/10.1109/TMM.2023.3310282
Wang RFeng JZhang FLuo XLuo Y(2024)Modality-Aware Heterogeneous Graph for Joint Video Moment Retrieval and Highlight DetectionIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2024.338902434:9(8896-8911)Online publication date: Sep-2024
https://doi.org/10.1109/TCSVT.2024.3389024
Chen CChen TJiang MLiu BJou JLien CChu SWen C(2024)The Deep Learning-Based Semantic Cross-Modal Moving-Object Moment Retrieval System2024 10th International Conference on Applied System Innovation (ICASI)10.1109/ICASI60819.2024.10547990(134-136)Online publication date: 17-Apr-2024
https://doi.org/10.1109/ICASI60819.2024.10547990
Wu ZJiang YWu ZJiang Y(2024)Deep Learning for Video LocalizationDeep Learning for Video Understanding10.1007/978-3-031-57679-9_4(39-68)Online publication date: 28-Mar-2024
https://doi.org/10.1007/978-3-031-57679-9_4
Roy CNourani MArya SShanbhag MRahman TRagan ERuozzi NGogate V(2023)Explainable Activity Recognition in Videos using Deep Learning and Tractable Probabilistic ModelsACM Transactions on Interactive Intelligent Systems10.1145/362696113:4(1-32)Online publication date: 12-Oct-2023
https://dl.acm.org/doi/10.1145/3626961
Wang XWu ZChen HLan XZhu WEl Saddik AMei TCucchiara RBertini MTobon Vallejo DAtrey PHossain M(2023)Mixup-Augmented Temporally Debiased Video Grounding with Content-Location DisentanglementProceedings of the 31st ACM International Conference on Multimedia10.1145/3581783.3612401(4450-4459)Online publication date: 26-Oct-2023
https://dl.acm.org/doi/10.1145/3581783.3612401
Lan XYuan YWang XChen LWang ZMa LZhu W(2023)A Closer Look at Debiased Temporal Sentence Grounding in Videos: Dataset, Metric, and ApproachACM Transactions on Multimedia Computing, Communications, and Applications10.1145/356557319:6(1-23)Online publication date: 12-Jul-2023
https://dl.acm.org/doi/10.1145/3565573
Liu MNie LWang YWang MRui Y(2023)A Survey on Video Moment LocalizationACM Computing Surveys10.1145/355653755:9(1-37)Online publication date: 16-Jan-2023
https://dl.acm.org/doi/10.1145/3556537
Zheng QDong JQu XYang XWang YZhou PLiu BWang X(2023)Progressive Localization Networks for Language-Based Moment LocalizationACM Transactions on Multimedia Computing, Communications, and Applications10.1145/354385719:2(1-21)Online publication date: 6-Feb-2023
https://dl.acm.org/doi/10.1145/3543857
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