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Human emotion recognition in images based on text-image contrastive fusion

Tian Yule
Wang Yiding
SchoolofInformation, North China UniversityofTechnology, Beijing 100144, China

Abstract

Context-based recognition of human emotions in images has become an increasingly popular task in recent years, with application value in many fields. Most existing methods only encode the human subject and the background separately, extracting isolated features for simple interaction, lacking an effective feature fusion mechanism between the subject and the contextual background, this paper aims to address the issue of the interaction between complex backgrounds and the human subject. This paper proposes a new network for human emotion recognition in images based on text-image contrastive fusion. First, designing prompt words to extract textual descriptions of the emotional state between the contextual background and the target human subject by fully utilizes the extensive social context information and reasoning capabilities of large visual-language models.Secondly, proposed a text-image contrastive fusion module, which fuses the cropped target human subject image features with the text description features obtained based on the prompt words through this module. Finally, the fusion algorithm introduces a contrastive loss function to unify the representation of image encoding and text encoding, allowing for more accurate capture of effective emotional expressions during fusion. Experimental results show that the network can learn more effective emotional feature representations, and the network achieves superior results on the EMOTIC dataset with an mAP of 37.30%. The method proposed in this paper better integrates the features of the human subject and the background in the image, thereby improving the accuracy of human emotion recognition in images.

Foundation Support

国家自然科学基金资助项目(62276018)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2024.12.0497
Publish at: Application Research of Computers Accepted Paper, Vol. 42, 2025 No. 7

Publish History

[2025-03-14] Accepted Paper

Cite This Article

田雨乐, 王一丁. 基于图文对比融合的图像人物情感识别 [J]. 计算机应用研究, 2025, 42 (7). (2025-03-14). https://doi.org/10.19734/j.issn.1001-3695.2024.12.0497. (Tian Yule, Wang Yiding. Human emotion recognition in images based on text-image contrastive fusion [J]. Application Research of Computers, 2025, 42 (7). (2025-03-14). https://doi.org/10.19734/j.issn.1001-3695.2024.12.0497. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.


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