research-article

Similar Scenes Arouse Similar Emotions: Parallel Data Augmentation for Stylized Image Captioning

Authors:

Yin ZhangAuthors Info & Claims

MM '21: Proceedings of the 29th ACM International Conference on Multimedia

October 2021

Pages 5363 - 5372

https://doi.org/10.1145/3474085.3475662

Published: 17 October 2021 Publication History

Abstract

Stylized image captioning systems aim to generate a caption not only semantically related to a given image but also consistent with a given style description. One of the biggest challenges with this task is the lack of sufficient paired stylized data. Many studies focus on unsupervised approaches, without considering from the perspective of data augmentation. We begin with the observation that people may recall similar emotions when they are in similar scenes, and often express similar emotions with similar style phrases, which underpins our data augmentation idea. In this paper, we propose a novel Extract-Retrieve-Generate data augmentation framework to extract style phrases from small-scale stylized sentences and graft them to large-scale factual captions. First, we design the emotional signal extractor to extract style phrases from small-scale stylized sentences. Second, we construct the plugable multi-modal scene retriever to retrieve scenes represented with pairs of an image and its stylized caption, which are similar to the query image or caption in the large-scale factual data. In the end, based on the style phrases of similar scenes and the factual description of the current scene, we build the emotion-aware caption generator to generate fluent and diversified stylized captions for the current scene. Extensive experimental results show that our framework can alleviate the data scarcity problem effectively. It also significantly boosts the performance of several existing image captioning models in both supervised and unsupervised settings, which outperforms the state-of-the-art stylized image captioning methods in terms of both sentence relevance and stylishness by a substantial margin.

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Cited By

Song PGuo DYang XTang SWang M(2024)Emotional Video Captioning With Vision-Based Emotion Interpretation NetworkIEEE Transactions on Image Processing10.1109/TIP.2024.335904533(1122-1135)Online publication date: 1-Feb-2024
https://dl.acm.org/doi/10.1109/TIP.2024.3359045
Wang LQiu HQiu BMeng FWu QLi H(2024)TridentCap: Image-Fact-Style Trident Semantic Framework for Stylized Image CaptioningIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2023.331513334:5(3563-3575)Online publication date: May-2024
https://doi.org/10.1109/TCSVT.2023.3315133
Yongqiang ZZhi JFeng ZHaiyan ZZhengwei TChengfeng DXinhai XDonghong L(2023)Deep-learning-based image captioning:analysis and prospectsJournal of Image and Graphics10.11834/jig.22066028:9(2788-2816)Online publication date: 2023
https://doi.org/10.11834/jig.220660
Show More Cited By

Index Terms

Similar Scenes Arouse Similar Emotions: Parallel Data Augmentation for Stylized Image Captioning
1. Information systems
  1. Information systems applications
    1. Multimedia information systems
      1. Multimedia content creation

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cover image ACM Conferences

MM '21: Proceedings of the 29th ACM International Conference on Multimedia

October 2021

5796 pages

ISBN:9781450386517

DOI:10.1145/3474085

General Chairs:
Heng Tao Shen
University of Electronic Science&Technology of China, China
,
Yueting Zhuang
Zhejiang University, China
,
John R. Smith
IBM, USA
,
Program Chairs:
Yang Yang
University of Electronic Science and Technology of China, China
,
Pablo Cesar
CWI&TU Delft, The Netherlands
,
Florian Metze
FACEBOOK, Inc., USA
,
Balakrishnan Prabhakaran
University of Texas at Dallas, USA

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Published: 17 October 2021

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Alibaba-Zhejiang University Joint Institute of Frontier Technologies
MoE Engineering Research Center of Digital Library
the Fundamental Research Funds for the Central Universities.
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Chinese Knowledge Center for Engineering Sciences and Technology

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MM '21: ACM Multimedia Conference

October 20 - 24, 2021

Virtual Event, China

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Overall Acceptance Rate 995 of 4,171 submissions, 24%

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The 32nd ACM International Conference on Multimedia

October 28 - November 1, 2024

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Cited By

Song PGuo DYang XTang SWang M(2024)Emotional Video Captioning With Vision-Based Emotion Interpretation NetworkIEEE Transactions on Image Processing10.1109/TIP.2024.335904533(1122-1135)Online publication date: 1-Feb-2024
https://dl.acm.org/doi/10.1109/TIP.2024.3359045
Wang LQiu HQiu BMeng FWu QLi H(2024)TridentCap: Image-Fact-Style Trident Semantic Framework for Stylized Image CaptioningIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2023.331513334:5(3563-3575)Online publication date: May-2024
https://doi.org/10.1109/TCSVT.2023.3315133
Yongqiang ZZhi JFeng ZHaiyan ZZhengwei TChengfeng DXinhai XDonghong L(2023)Deep-learning-based image captioning:analysis and prospectsJournal of Image and Graphics10.11834/jig.22066028:9(2788-2816)Online publication date: 2023
https://doi.org/10.11834/jig.220660
Luo TZhang XPeng JWang DZhou W(2023)Emotion Interpretational Caption of Art Visual based on Reinforcement Learning2023 2nd International Conference on Image Processing and Media Computing (ICIPMC)10.1109/ICIPMC58929.2023.00021(82-88)Online publication date: 26-May-2023
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Sharma DDhiman CKumar D(2023)Evolution of visual data captioning Methods, Datasets, and evaluation MetricsExpert Systems with Applications: An International Journal10.1016/j.eswa.2023.119773221:COnline publication date: 1-Jul-2023
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Duan YWang ZLi YWang J(2023)Cross-domain multi-style merge for image captioningComputer Vision and Image Understanding10.1016/j.cviu.2022.103617228:COnline publication date: 1-Feb-2023
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Cornia MBaraldi LFiameni GCucchiara R(2023)Generating More Pertinent Captions by Leveraging Semantics and Style on Multi-Source DatasetsInternational Journal of Computer Vision10.1007/s11263-023-01949-w132:5(1701-1720)Online publication date: 5-Dec-2023
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Wu XLi T(2023)Sentimental Visual Captioning using Multimodal TransformerInternational Journal of Computer Vision10.1007/s11263-023-01752-7131:4(1073-1090)Online publication date: 6-Feb-2023
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Sharma DDhiman CKumar D(2022)A Review of Stylized Image Captioning Techniques, Evaluation Parameters, and Datasets2022 4th International Conference on Artificial Intelligence and Speech Technology (AIST)10.1109/AIST55798.2022.10064842(1-5)Online publication date: 9-Dec-2022
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Duan YWang ZYi LWang J(undefined)Cross-Domain Multi-Style Merge for Image CaptioningSSRN Electronic Journal10.2139/ssrn.4162675
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