HEC-Net: Hierarchical Event-RGB Cross-Modal Fusion for Single-Eye Emotion Recognition

Sichen Shao; Bohan Liang; Jie Zhang; Junjie Cao

doi:10.54254/2753-8818/2026.31464

Article Information

Received: 22 January 2026

Published: 26 January 2026

DOI: https://doi.org/10.54254/2753-8818/2026.31464

Article Type: Research Article

Cite this article

Shao,S.;Liang,B.;Zhang,J.;Cao,J. (2026). HEC-Net: Hierarchical Event-RGB Cross-Modal Fusion for Single-Eye Emotion Recognition. Theoretical and Natural Science,159,1-7.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About this Volume

Volume Title: TNS Vol.159

Part of Series: Theoretical and Natural Science

ISSN: 2753-8818 (Print) / 2753-8826 (Online)

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[1]Wu H, Feng J and Tian X, et al. “Emo: real-time emotion recognition from single-eye images for resource-constrained eyewear devices, ” In Proc. ACM MobiSys, 448-461, 2020.

[2]Hickson S, Dufour N and Sud A, et al. “Eyemotion: classifying facial expressions in vr using eye-tracking cameras, ” In Proc. IEEE WACV, pp. 1626-1635, 2019.

[3]Gallego G, Delbrück T and Orchard G, et al. “Event-based vision: a survey, ” IEEE Trans. Pattern Anal. Mach. Intell., vol. 44, no. 1, pp. 154-180, 2020.

[4]Zhang H, Zhang J and Dong B, et al. “In the blink of an eye: event-based emotion recognition, ”ACM SIGGRAPH Conf. Proc., Article 1, pp. 1-11, 2023.

[5]Han R, Liu X and Zhang Y, et al. “Hierarchical event-rgb interaction network for single-eye expression recognition, ” Inf. Sci., vol. 690, Art. no. 121539, 2024.

[6]He K, Zhang X, Ren S, and Sun J. “Deep residual learning for image recognition, ” In Proc. IEEE/CVF Conf. Comput. Vis. Pattern Recognit. (CVPR), pp. 770-778, 2016.

[7]Yan W, Li X, Wang S, Zhao G, Liu Y, and Chen Y. “Casme II: an improved spontaneous micro-expression database and the baseline evaluation, ” PLoS ONE, vol. 9, no. 1, p. e86041, 2014.

[8]Lin J, Gan C, and Han S. “TSM: temporal shift module for efficient video understanding, ” In Proc. IEEE/CVF Int. Conf. Comput. Vis. (ICCV), pp. 7083-7093, 2019.

[9]Liu Z, Lin Y and Cao Y, et al. “Swin transformer: hierarchical vision transformer using shifted windows, ” In Proc. IEEE/CVF Int. Conf. Comput. Vis. (ICCV), pp. 10012-10022, 2021.

[10]Yang J, Li C, Zhang P, et al. “Focal self-attention for local-global interactions in vision transformers, ” In Adv. Neural Inf. Process. Syst. (NeurIPS), vol. 34, pp. 30013–30025, 2021.