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👯 My current research direction is Long-tailed Visual Recognition and 3D Point Cloud Analysis. If you are interested in and looking for cooperation, please feel free to contact me.

👯looking for cooperation ✨✨

Department of Computer Science, Hong Kong Baptist University 2018.11-2022.09

• Major: Computer Science,
• Research Direction: Computer vision, pattern recognition, image generation,
• Principle Supervisor: Prof. CHEUNG Yiu-ming,
• Thesis title: Advances in Long-Tailed Visual Recognition

School of Electronic Engineering, Key Laboratory of Radar Signal Processing (RSP), Xidian University 2015.09-2018.06

• Major: Signal and Information Processing
• Principle Supervisor: Prof. LI Ming
• Thesis title: Research of Airborne High Resolution SAR Imaging and Location Techniques

Hanhong College (The Department for Innovative Talents Training), Southwest University, Chongqing 2011.09-2015.06

• Major: Communication Engineering

• 12/2022-present, Associate Researcher, Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), work with the Visual Computing Research Center (VCC) (headed by Prof. Hui Huang) at the College of Computer Science & Software Engineering, Shenzhen University.
• 09/2022-12/2022 HKBU Institute for Research and Countuning Education (IRACE), Senior RA.

• M.K. Li, Y. Liu, Y. Lu, Y. Zhang, Y.-m. Cheung, H. Huang*, Improving Visual Prompt Tuning by Gaussian Neighborhood Minimization for Long-Tailed Visual Recognition, in NeurIPS, 2024.
• M.K. Li, D. Li, G.Q. Yang, Y.-m. Cheung, H. Huang*, Adapt PointFormer: 3D Point Cloud Analysis via Adapting 2D Visual Transformers, in ECAI, 2024.
• C.X. Hong, Y. Jin, Z.Q. Kang, Y.Z. Chen, M.K. Li, Yang Lu, Hanzi Wang, Dynamically Anchored Prompting for Task-Imbalanced Continual Learning, in IJCAI, 2024.
• Z.K. Hu, Y.M. Cheung, M.K. Li, W.C. Lan, D.L. Zhang, Key Points Centered Sparse Hashing for Cross-Modal Retrieval, in Proceedings of 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP’24), Seoul, Korea, April 14-19, 2024.
• M.K. Li, Z.K. Hu, Y. Lu, W.C. Lan, Y.M. Cheung and H. Huang, Feature Fusion from Head to Tail for Long-Tailed Visual Recognition, in Proceedings of Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI’24), Vancouver, Canada, February 20-27, 38(12), pp. 13581-13589, 2024, . [overall acceptance rate: 23.75%].
• Z.K. Hu, Y.M. Cheung, M.K. Li and W.C. Lan, Few-shot Lip-password Based Speaker Verification, in Proceedings of 2023 International Conference on Image Processing (ICIP’2023), Kuala Lumpur, Malaysia, October 8-11, 2023, pp. 1960-1964.
• Y. Jin, M.K. Li, Y. Lu, Y.M. Cheung and H.Z. Wang, Long-Tailed Visual Recognition via Self-Heterogeneous Integration with Knowledge Excavation, in Proceedings of the Thirty-Fourth IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR), Vancouver, Canada, June 18-22, 2023, poster, pp. 23695-23704.
• M.K. Li, Y.M. Cheung, Y. Lu, Long-tailed visual recognition via gaussian clouded logit adjustment, in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 6929-6938, poster, 2022.
• M.K. Li, Y.M. Cheung, J.Y. Jiang, Feature-Balanced Loss for Long-Tailed Visual Recognition, 2022 IEEE International Conference on Multimedia and Expo (ICME), oral, pp. 1-6, 2022.
• Y.M. Cheung, M.K. Li, R. Zou, Facial Structure Guided GAN for Identity-preserved Face Image De-occlusion, in Proceedings of the 2021 International Conference on Multimedia Retrieval (ICMR), oral, pp. 46-54, 2021.
• M. Pang, Y.M. Cheung, Q.Q. Shi, M.K. Li, Iterative dynamic generic learning for single sample face recognition with a contaminated gallery, in 2020 IEEE International Conference on Multimedia and Expo (ICME), oral, pp. 1-6, 2020.

• Z.K. Hu, Y.M. Cheung, M.K. Li and W.C. Lan, Cross-Modal Hashing Method with Properties of Hamming Space: A New Perspective, IEEE Transactions on Pattern Analysis and Machine Intelligence, in press, DOI: 10.1109/TPAMI.2024.3392763.
• W.C. Lan, Y.M. Cheung, J.Y. Jiang, Z.K. Hu and M.K. Li, Compact Neural Network via Stacking Hybrid Units, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), in press, DOI: 10.1109/TPAMI.2023.3323496
• Z.K. Hu, Y.M. Cheung, M.K. Li, W.C. Lan, D.L. Zhang and Q. Liu, Joint Semantic Preserving Sparse Hashing for Cross-Modal Retrieval, IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), in press, DOI: 10.1109/TCSVT.2023.3307608.
• M.K. Li, Y.M. Cheung, Z.K. Hu, Key Point Sensitive Loss for Long-tailed Visual Recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 45 (4), pp.4812-4825, 2022.
• M.K. Li, Y.M. Cheung, Identity-Preserved Complete Face Recovering Network for Partial Face Image, IEEE Transactions on Emerging Topics in Computational Intelligence (TETCI), 7 (2), pp.604-609, 2023.
• M Pang, YM Cheung, Q Shi, M.K. Li, Iterative dynamic generic learning for face recognition from a contaminated single-sample per person, IEEE Transactions on Neural Networks and Learning Systems 32 (4), pp.1560-1574, 2020.
• M.K. Li, M. Li, P. Zhang, Y. Wu, W.Y. Song, L. An, SAR image change detection using PCANet guided by saliency detection, IEEE Geoscience and Remote Sensing Letters, 16 (3), pp.402-406, 2018.

• PC member of ICDCS 2024, ECAI 2024, AAAI 2024.

• ICCV 2023, CVPR 2023 2024, NeurIPS 2024
• IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
• IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
• IEEE Transactions on Industrial Informatics (TII)
• IEEE Transactions on Emerging Topics in Computational Intelligence (TETCI)

• 2022/23 Outstanding Staff Award by Guangming Lab. Link
• 2021/22 Computer Science Department RPg Performance Award, Hong Kong Baptist University. Link
• 2021/22 Champion of Postgraduate Student Research Paper Competition. Awarded by IEEE (Hong Kong) Computational Intelligence Chapter.
• 2020 Second Runners-up of Virtual NetHack Contest during the IEEE Region 10 Students Young Professionals Women in Engineering Life members (SYWL) Virtual Congress}. Awarded by IEEE Region 10.

• 📫 Email: [email protected]

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