Yang Liu | Pattern Recognition | Innovative Research Award

Published on by Database Scientist

Assist. Prof. Dr. Yang Liu | Pattern Recognition | Innovative Research Award

Assistant professor at Zhejiang University | China

Assistant Professor Dr. Yang Liu is an emerging scholar specializing in computer vision, machine learning, and remote sensing, with a strong research focus on unsupervised representation learning, facial modeling, and multimodal image translation. His work integrates deep learning and generative modeling to advance intelligent visual understanding systems. Notably, his 2025 paper “Adaptive Sparse Contrastive Learning for Unsupervised Object Re-identification” in Pattern Recognition introduces an innovative sparse contrastive framework for improved feature discrimination in object re-identification. His 2024 studies in Knowledge-Based Systems and Remote Sensing present significant contributions to multi-objective reinforcement learning through dynamic preference inference and to SAR-to-multispectral image translation via S2MS-GAN, enhancing cross-modal synthesis and efficiency. Earlier works in IEEE Signal Processing Letters and IEEE Access showcase his expertise in fine-scale 3D face reconstruction, texture fusion, and photorealistic head modeling. Collaborating with international teams from leading universities such as Zhejiang University and Northwestern Polytechnical University, Assistant Professor Dr. Yang Liu continues to drive innovation at the intersection of computer vision and AI. His ongoing research aims to develop more adaptive, interpretable, and sustainable AI-driven visual intelligence systems that can bridge the gap between human perception and machine understanding in complex, real-world environments.

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Featured Publications

  • Zheng, D., Liu, Y., Zhou, D., Xiao, J., Zhang, B., & Chen, L. (2025). Adaptive sparse contrastive learning for unsupervised object re-identification. Pattern Recognition, 157, 112604.

  • Liu, Y., Zhou, Y., He, Z., Yang, Y., Han, Q., & Li, J. (2024). Dynamic preference inference network: Improving sample efficiency for multi-objective reinforcement learning by preference estimation. Knowledge-Based Systems, 305, 112512.

  • Liu, Y., Han, Q., Yang, H., & Hu, H. (2024). High-resolution SAR-to-multispectral image translation based on S2MS-GAN. Remote Sensing, 16(21), 4045.

  • Liu, Y., Fan, Y., Guo, Z., Zaman, A., & Liu, S. (2023). Fine-scale face fitting and texture fusion with inverse renderer. IEEE Signal Processing Letters, 30, 139–143.

  • Fan, Y., Liu, Y., Lv, G., Liu, S., Li, G., & Huang, Y. (2020). Full face-and-head 3D model with photorealistic texture. IEEE Access, 8, 188041–188051.