short-paper

VideoCLIP: A Cross-Attention Model for Fast Video-Text Retrieval Task with Image CLIP

Authors:

Chiuman HoAuthors Info & Claims

ICMR '22: Proceedings of the 2022 International Conference on Multimedia Retrieval

Pages 29 - 33

https://doi.org/10.1145/3512527.3531429

Published: 27 June 2022 Publication History

Abstract

Video-text retrieval is an essential task in cross-modal information retrieval, i.e., retrieving relevant videos from a large and unlabelled dataset given textual queries. Existing methods that simply pool the image features (e.g., based on the CLIP encoder [14]) from frames to build the video descriptor often result in sub-optimal video-text search accuracy since the information among different modalities is not fully exchanged and aligned. In this paper, we proposed a novel dual-encoder model to address the challenging video-text retrieval problem, which uses a highly efficient cross-attention module to facilitate the information exchange between multiple modalities (i.e., video and text). The proposed VideoCLIP is evaluated on two benchmark video-text datasets, MSRVTT and DiDeMo, and the results show that our model can outperform existing state-of-the-art methods while the retrieval speed is much faster than the traditional query-agnostic search model.

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Cited By

Zhu JShen XMehta SAbeo TZhan Y(2024)Self-expressive induced clustered attention for video-text retrievalMultimedia Systems10.1007/s00530-024-01549-930:6Online publication date: 27-Nov-2024
https://doi.org/10.1007/s00530-024-01549-9
Jiang CLiu HYu XWang QCheng YXu JLiu ZGuo QChu WYang MQi YEl Saddik AMei TCucchiara RBertini MTobon Vallejo DAtrey PHossain M(2023)Dual-Modal Attention-Enhanced Text-Video Retrieval with Triplet Partial Margin Contrastive LearningProceedings of the 31st ACM International Conference on Multimedia10.1145/3581783.3612006(4626-4636)Online publication date: 26-Oct-2023
https://dl.acm.org/doi/10.1145/3581783.3612006
Hazra RChen BRai AKamra NDesai R(2023)EgoTV: Egocentric Task Verification from Natural Language Task Descriptions2023 IEEE/CVF International Conference on Computer Vision (ICCV)10.1109/ICCV51070.2023.01414(15371-15383)Online publication date: 1-Oct-2023
https://doi.org/10.1109/ICCV51070.2023.01414

Index Terms

VideoCLIP: A Cross-Attention Model for Fast Video-Text Retrieval Task with Image CLIP
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 '22: Proceedings of the 2022 International Conference on Multimedia Retrieval

June 2022

714 pages

ISBN:9781450392389

DOI:10.1145/3512527

General Chairs:
Vincent Oria
New Jersey Institute of Technology, USA
,
Maria Luisa Sapino
Università degli Studi di Torino, Italy
,
Shin'ichi Satoh
National Institute of Informatics, Japan
,
Brigitte Kerhervé
Université du Québec à Montréal, Canada
,
Program Chairs:
Wen-Huang Cheng
National Yang Ming Chao Tung University, Taiwan
,
Ichiro Ide
Nagoya University, Japan
,
Vivek Singh
Rutgers University, USA

Copyright © 2022 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGMM: ACM Special Interest Group on Multimedia

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New York, NY, United States

Publication History

Published: 27 June 2022

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ICMR '22

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SIGMM

ICMR '22: International Conference on Multimedia Retrieval

June 27 - 30, 2022

NJ, Newark, USA

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Overall Acceptance Rate 254 of 830 submissions, 31%

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Cited By

Zhu JShen XMehta SAbeo TZhan Y(2024)Self-expressive induced clustered attention for video-text retrievalMultimedia Systems10.1007/s00530-024-01549-930:6Online publication date: 27-Nov-2024
https://doi.org/10.1007/s00530-024-01549-9
Jiang CLiu HYu XWang QCheng YXu JLiu ZGuo QChu WYang MQi YEl Saddik AMei TCucchiara RBertini MTobon Vallejo DAtrey PHossain M(2023)Dual-Modal Attention-Enhanced Text-Video Retrieval with Triplet Partial Margin Contrastive LearningProceedings of the 31st ACM International Conference on Multimedia10.1145/3581783.3612006(4626-4636)Online publication date: 26-Oct-2023
https://dl.acm.org/doi/10.1145/3581783.3612006
Hazra RChen BRai AKamra NDesai R(2023)EgoTV: Egocentric Task Verification from Natural Language Task Descriptions2023 IEEE/CVF International Conference on Computer Vision (ICCV)10.1109/ICCV51070.2023.01414(15371-15383)Online publication date: 1-Oct-2023
https://doi.org/10.1109/ICCV51070.2023.01414

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