李婧婷

关于我

李婧婷，中国科学院心理研究所副研究员，博士生导师。获聘中国科学院心理研究所所特聘骨干岗位，入选2023年中国科学院青年创新促进会成员。主持国家自然面上、青基等科研项目，于IEEETPAMI、TAC、TIP、ICCV、ACMMM等国内外期刊、会议发表微表情相关论文多篇，两篇论文进入ESI高被引论文清单。相关研究成果获2023年北京市科学技术奖自然科学奖二等奖。连续四年担任ACMMM 微表情国际挑战赛主席，担任PRL等期刊客座编委、TPAMI、TAC、TIP、TCSVT、Neurocomputing等期刊审稿人。主要研究方向包括计算机视觉、情感计算，特别是智能人脸微表情分析。

教育与工作经历

  • 2022.07 - 至今: 中国科学院心理研究所, 副研究员
  • 2020.02 - 2022.06: 中国科学院心理研究所, 普通博士后
  • 2016.10 - 2019.12: 法国中央高等电力学校 (CentraleSupélec), 博士
  • 2013.09 - 2016.07: 北京航空航天大学, 硕士
  • 2009.09 - 2013.07: 北京航空航天大学, 学士

科研项目

项目

  • 面向特定应用场景的高生态效度微表情智能分析研究 (国家自然科学基金委员会, 面上项目), 2025-2028
  • 基于认知注意的多分支自监督学习的微表情检测方法研究 (国家自然科学基金委员会, 青年科学基金项目), 2022-2024
  • 中国科学院青年创新促进会第13批会员人才专项经费, 2023-2026
  • 谎言识别-人脸微表情分析 (中国科学院特别研究助理资助项目), 2022-2023
  • 基于多特征混合自监督学习模型的人脸微表情分析 (中国博士后科学基金, 第68批面上资助), 2020-2022
  • 基于面部微表情检测的谎言识别研究 (中国人民公安大学公共实验室开放课题), 2021-2022

参与项目

  • 基于面部表情和面部肌电跨模态分析的微表情数据标注问题研究 (家自然科学基金委员会, 面上项目), 2023-2026
  • 心理技术实验室二期专用硬件和软件开发 (国家部委), 2024-2025
  • 易感特质群体快感缺失的多维特征识别与干预 (中国科学院心理研究所揭榜挂帅项目), 2022-2023
  • 面向社会公共安全的隐藏情绪分析与识别方法研究 (国家自然科学基金委员会, 联合基金项目), 2020-2023

学术兼职

期刊客座编委

  • Electronics - "Facial-Based Emotion Recognition: Challenges and Advances in Computer Vision" 专刊, 首席客座编委 (2024至今)
  • Frontiers in Robotics and AI - “Perceiving, Generating, and Interpreting Affect in Human-Robot Interaction (HRI)”专刊, 客座编委 (2023至今)
  • Pattern Recognition Letters - "Face based Emotion Understanding" 专刊, 客座编委 (2022-2023)

学会委员

  • 中国图象图形学会 (CS): 机器视觉专委会委员 (2020至今), 情感计算与理解专委会委员 (2021至今), 女科技工作者委员会委员 (2023至今)
  • 中国计算机学会 (CCF): 人机交互专委会委员 (2022至今), 计算机视觉专委会委员 (2022至今)
  • 中文信息学会 (CIPS): 情感计算专委会委员 (2024至今)
  • 中国人工智能学会 (CAAI): 情感智能专委会委员 (2025至今)

学术出版

[1] Fan, X., Li, J., See, J., Yap, M. H., Cheng, W.-H., Li, X., Hong, X., Wang, S.-J., & Davision, A. K. (2025). MEGC2025: Micro-Expression Grand Challenge on Spot Then Recognize and Visual Question Answering. arXiv preprint arXiv:250606.15298. [ PDF ]

[2] Li, J., Lu, S., Wang, Y., Dong, Z., Wang, S.-J., & Fu, X. (2025). Could Micro-Expressions be Quantified? Electromyography Gives Affirmative Evidence. IEEE Transactions on Affective Computing, 1-16. https://doi.ieeecomputersociety.org/10.1109/TAFFC.2025.3575127 [ PDF ]

[3] Li, J., Wang, S.-J., Wang, Y., Zhou, H., & Fu, X. (2025). Parallel Spatiotemporal Network to recognize micro-expression. Neurocomputing, 636, 129891. [ PDF ]

[4] Li, J., Zhou, H., Qian, Y., Dong, Z., & Wang, S.-J. (2025). Micro-expression recognition using dual-view self-supervised contrastive learning with intensity perception. Neurocomputing, 619, 129142. [ PDF ]

[5] Wang, S.-J., Miao, Y.-H., Li, J., Zhou, L., Dong, Z., Sun, M., & Fu, X. (2025). Micro-Expression Key Frame Inference. IEEE Transactions on Affective Computing. [ PDF ]

[6] See, J., Li, J., Davison, A. K., Liong, G. B., Yap, M. H., Cheng, W.-H., Li, X., Hong, X., & Wang, S.-J. (2024). MEGC2024: ACM Multimedia 2024 Facial Micro-Expression Grand Challenge. In Proceedings of the 32nd ACM International Conference on Multimedia (pp. 11482-11483). [ PDF ]

[7] Sun, Q., Hu, Y., Fan, M., Li, J., & Wang, S.-J. (2024). “Can It Be Customized According to My Motor Abilities?”: Toward Designing User-Defined Head Gestures for People with Dystonia. In Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems (pp. 1-11). [ PDF ]

[8] Wang, S.-J., Wang, Y., Li, J., Dong, Z., Zhang, J., & Liu, Y. (2024). Cross-modal analysis of facial EMG in micro-expressions and data annotation algorithm. Advances in Psychological Science, 32(1), 1. [ PDF ]

[9] Wang, Y., Sun, M., Kang, X., Li, J., Guo, P., Gao, M., & Wang, S.-J. (2024). CDSD: Chinese Dysarthria Speech Database. In Interspeech 2024 (pp. 4109-4113). doi: 10.21437/Interspeech.2024-1597 [ PDF ]

[10] Davison, A. K., Li, J., Yap, M. H., See, J., Cheng, W.-H., Li, X., Hong, X., & Wang, S.-J. (2023). FME'23: 3rd Facial Micro-Expression Workshop. In Proceedings of the 31st ACM International Conference on Multimedia (pp. 9736-9738). [ PDF ]

[11] Davison, A. K., Li, J., Yap, M. H., See, J., Cheng, W.-H., Li, X., Hong, X., & Wang, S.-J. (2023). Megc2023: Acm multimedia 2023 me grand challenge. In Proceedings of the 31st ACM International Conference on Multimedia (pp. 9625-9629). [ PDF ]

[12] Li, J., Yap, M. H., Cheng, W.-H., See, J., Hong, X., Li, X., & Wang, S.-J. (2023). Editorial for pattern recognition letters special issue on face-based emotion understanding. Pattern Recognition Letters. [ PDF ]

[13] Yang, X., Yang, H., Li, J., & Wang, S.-J. (2023). Simple but effective in-the-wild micro-expression spotting based on head pose segmentation. In Proceedings of the 3rd Workshop on Facial Micro-Expression: Advanced Techniques for Multi-Modal Facial Expression Analysis (pp. 9-16). [ PDF ]

[14] Zhang, J., Huang, S., Li, J., Wang, Y., Dong, Z., & Wang, S.-J. (2023). A perifacial EMG acquisition system for facial-muscle-movement recognition. Sensors, 23(21), 8758. [ PDF ]

[15] Zhou, H., Huang, S., Li, J., & Wang, S.-J. (2023). Dual-ATME: Dual-Branch Attention Network for Micro-Expression Recognition. Entropy, 25(3), 460. [ PDF ]

[16] Dong, Z., Wang, G., Lu, S., Li, J., Yan, W., & Wang, S.-J. (2022). Spontaneous facial expressions and micro-expressions coding: from brain to face. Frontiers in Psychology, 12, 784834. [ PDF ]

[17] Li, J., Dong, Z., Lu, S., Wang, S.-J., Yan, W.-J., Ma, Y., Liu, Y., Huang, C., & Fu, X. (2022). CAS (ME) 3: A third generation facial spontaneous micro-expression database with depth information and high ecological validity. IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(3), 2782-2800. [ PDF ]

[18] Li, J., Wang, T., & Wang, S.-J. (2022). Facial micro-expression recognition based on deep local-holistic network. Applied Sciences, 12(9), 4643. [ PDF ]

[19] Li, J., Yap, M. H., Cheng, W.-H., See, J., Hong, X., Li, X., & Wang, S.-J. (2022). FME'22: 2nd Workshop on Facial Micro-Expression: Advanced Techniques for Multi-Modal Facial Expression Analysis. In Proceedings of the 30th ACM International Conference on Multimedia (pp. 7397-7399). [ PDF ]

[20] Li, J., Yap, M. H., Cheng, W.-H., See, J., Hong, X., Li, X., Wang, S.-J., Davison, A. K., Li, Y., & Dong, Z. (2022). MEGC2022: ACM multimedia 2022 micro-expression grand challenge. In Proceedings of the 30th ACM International Conference on Multimedia (pp. 7170-7174). [ PDF ]

[21] Lu, S., Li, J., Wang, Y., Dong, Z., Wang, S.-J., & Fu, X. (2022). A more objective quantification of micro-expression intensity through facial electromyography. In Proceedings of the 2nd Workshop on Facial Micro-Expression: Advanced Techniques for Multi-Modal Facial Expression Analysis (pp. 11-17). [ PDF ]

[22] Lu, S., Li, J., Dong, Z., Wang, G., Li, Z., Ma, Y., Wang, S.-J., & Zhuang, D. (2022). 一项实证研究：高风险场景下微表情大概率出现的论证 (An Empirical Study: The Demonstration of High Probability of Micro-Expressions in High-Stakes Scenario). 中国人民公安大学学报(自然科学版) (Journal of People's Public Security University of China(Science and Technology)), 28(03), 23-31. [ PDF ]

[23] Yap, C. H., Yap, M. H., Davison, A., Kendrick, C., Li, J., Wang, S.-J., & Cunningham, R. (2022). 3d-cnn for facial micro-and macro-expression spotting on long video sequences using temporal oriented reference frame. In Proceedings of the 30th ACM International Conference on Multimedia (pp. 7016-7020). [ PDF ]

[24] 李婧婷, 东子朝, 刘烨, 王甦菁, & 庄东哲. (2022). 基于人类注意机制的微表情检测方法. 心理科学进展, 30(10), 2143. [ PDF ]

[25] Li, J., Yap, M. H., Cheng, W.-H., See, J., Hong, X., Li, X., & Wang, S.-J. (2021). FME'21: 1st workshop on facial micro-expression: advanced techniques for facial expressions generation and spotting. In Proceedings of the 29th ACM International Conference on Multimedia (pp. 5700-5701). [ PDF ]

[26] Wang, S.-J., He, Y., Li, J., & Fu, X. (2021). MESNet: A convolutional neural network for spotting multi-scale micro-expression intervals in long videos. IEEE Transactions on Image Processing, 30, 3956-3969. [ PDF ]

[27] He, Y., Wang, S.-J., Li, J., & Yap, M. H. (2020). Spotting macro-and micro-expression intervals in long video sequences. In 2020 15th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2020) (pp. 742-748). IEEE. [ PDF ]

[28] Li, J., Wang, S.-J., Yap, M. H., See, J., Hong, X., & Li, X. (2020). Megc2020-the third facial micro-expression grand challenge. In 2020 15th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2020) (pp. 777-780). IEEE. [ PDF ]

[29] Li, J., Soladie, C., & Seguier, R. (2020). Local temporal pattern and data augmentation for spotting micro-expressions. IEEE Transactions on Affective Computing, 14(1), 811-822. [ PDF ]

[30] Zhang, L.-W., Li, J., Wang, S.-J., Duan, X.-H., Yan, W.-J., Xie, H.-Y., & Huang, S.-C. (2020). Spatio-temporal fusion for macro-and micro-expression spotting in long video sequences. In 2020 15th IEEE international conference on automatic face and gesture recognition (FG 2020) (pp. 734-741). IEEE. [ PDF ]

[31] Li, J. (2019). Facial Micro-Expression Analysis [Doctoral dissertation, CentraleSupélec]. [ PDF ]

[32] Li, J., Soladie, C., & Seguier, R. (2019). A Survey on Databases for Facial Micro-Expression Analysis. In VISIGRAPP (5: VISAPP) (pp. 241-248). [ PDF ]

[33] Li, J., Soladie, C., Séguier, R., Wang, S.-J., & Yap, M. H. (2019). Spotting micro-expressions on long videos sequences. In 2019 14th IEEE International conference on automatic face & gesture recognition (FG 2019) (pp. 1-5). IEEE. [ PDF ]

[34] See, J., Yap, M. H., Li, J., Hong, X., & Wang, S.-J. (2019). Megc 2019--the second facial micro-expressions grand challenge. In 2019 14th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2019) (pp. 1-5). IEEE. [ PDF ]

[35] Li, J., Soladie, C., & Seguier, R. (2018). Détection de Micro-expressions par Reconnaissance de Motif Local Temporel de Mouvements Faciaux. In Reconnaissance des Formes, Image, Apprentissage et Perception. [ PDF ]

[36] Li, J., Soladie, C., & Seguier, R. (2018). Ltp-ml: Micro-expression detection by recognition of local temporal pattern of facial movements. In 2018 13th IEEE international conference on automatic face & gesture recognition (FG 2018) (pp. 634-641). IEEE. [ PDF ]

[37] Weber, R., Li, J., Soladié, C., & Séguier, R. (2018). A survey on databases of facial macro-expression and micro-expression. In International Joint Conference on Computer Vision, Imaging and Computer Graphics (pp. 298-325). Springer International Publishing. [ PDF ]

[38] Li, J. T., Xu, H. P., Shan, L., Liu, W., & Chen, G. Z. (2016). An efficient compressive sensing based PS-DInSAR method for surface deformation estimation. Measurement Science and Technology, 27(11), 114001. [ PDF ]

[39] Li, J., & Xu, H. (2015). PS-DInSAR deformation velocity estimation by the compressive sensing. In 2015 IEEE International Conference on Imaging Systems and Techniques (IST) (pp. 1-5). IEEE. [ PDF ]