Multimedia Signal Processing and Hardware Aware Intelligent Systems Lab

K. Tian, H. Wang, Z. Wu, Y. Lyu, M. I. Vai, and Y. Liu, “Multibit Attention Fusion for Gaze Estimation Using 12-Bit RAW Data From CMOS Sensors,” IEEE Transactions on Instrumentation and Measurement, vol. 74, pp. 1–13, 2025, Art no. 5031413.

Sha T, Su J, Pun S, Liu Y, "Monocular 3D gaze estimation using feature discretization and attention mechanism," Optoelectronics Letters, vol. 19, no. 5, pp. 301-306, 2023.

J. Sun, Z. Wu, H. Wang, P. Jing, and Y. Liu, “A Novel Integrated Eye-Tracking System With Stereo Stimuli for 3-D Gaze Estimation,” IEEE Transactions on Instrumentation and Measurement, vol. 72, pp. 1–15, 2023.

李畅, 刘昱, 孙景林, “用于红外眼动图像分割的优化方法,” 激光与光电子学进展, 2022, 59(2): 0210016.

刘昱, 孙景林, "基于匹配特征的三维注视点估计及三维眼动模型建立方法," 专利号 ZL202110417364.X, 专利申请日: 2021年04月19日.

Y. Zhou, H. Zhang, Y. Sun, Y. Liu, and S. Y. Kung, “Illumination guided domain adaptation object detection in thermal imagery,” Neurocomputing, vol. 595, p. 131237, 2025.

J. Liu, H. Wang, R. Liu, S. Wang, and Y. Liu, “Sequential Spectral-Spatial Feature Convolution Network With Self-Attention for Remote Sensing Hyperspectral Image Classification,” IEEE Transactions on Geoscience and Remote Sensing, vol. 63, pp. 1–15, 2025, Art no. 5601815.

C. Kang, H. Wang, R. Liu, S. Wang, and Y. Liu, “CaFEN: A Causal Feature Embedding Network for Visible-Infrared Image Registration,” in 2025 44th Chinese Control Conference (CCC), Chongqing, China, July 2025.

T. Pan, Y. Wang, P. Jing, R. Ma, Z. Yi, and Y. Liu, “PairHuman: A high-fidelity photographic dataset for customized dual-person generation,” Information Fusion, vol. 107, p. 103984, 2025.

R. Liu, H. Wang, K. Hu, S. Wang, and Y. Liu, “F2Fusion: Frequency Feature Fusion Network for Infrared and Visible Image via Contourlet Transform and Mamba-UNet,” IEEE Transactions on Instrumentation and Measurement, vol. 74, pp. 1–17, 2025.

K. Hu, P. Jing, R. Liu, B. Wei, and Y. Liu, “Efficient learned image compression with dual-space aggregation transformer,” Digital Signal Processing, vol. 149, p. 105797, 2025.

K. Hu, H. Wang, Y. Lyu, R. Liu, and Y. Liu, “Text-guided ROI-based neural image compression,” IEEE Transactions on Broadcasting, 2025.

Wei Lu, Yujia Zhai, Jiaze Han, Peiguang Jing*, Yu Liu, Yuting Su. "VMemNet: A Deep Collaborative Spatial - Temporal Network with Attention Representation for Video Memorability Prediction," IEEE Transactions on Multimedia, 2024, 26: 4926 – 4937.

Renhe Liu, Yu Liu, Han Wang, Shan Du. "WaveFusionNet: Infrared and visible image fusion based on multi - scale feature encoder - decoder and discrete wavele decomposition," Optics Communications, Volume 573, 2024, https://doi.org/10.1016/j.optcom.2024.131024.

Peiguang Jing, Xuan Zhao, Fugui Fan, Fan Yang, Yun Li, Yuting Su. "Multimodal Progressive Modulation Network for Micro - video Multi - label Classification," IEEE Transactions on Multimedia, 2024, 26: 10134 - 10144.

Peiguang Jing, Haoyi Sun, Liqiang Nie, Yun Li, Yuting Su. "Deep Multi - modal Hashing with Semantic Enhancement for Multi - label Micro - video Retrieval," IEEE Transactions on Knowledge and Data Engineering, 2024, 36(10): 5080 - 5091.

Jing P, Liu X, Zhang L, Li Y, Liu Y, Su Y. "Multimodal Attentive Representation Learning for Micro-video Multi-label Classification," ACM Transactions on Multimedia Computing, Communications and Applications. 2024.

Yuting Su, Wei Zhao, Peiguang Jing*, Liqiang Nie. "Exploiting Low - rank Latent Gaussian Graphical Model Estimation for Visual Sentiment Distribution," IEEE Transactions on Multimedia, 2023, 25: 1243 - 1255.

Peiguang Jing, Xianyi Liu, Ji Wang, Yinwei Wei, Liqiang Nie, Yuting Su. "StyleEDL: Style - Guided High - order Attention Network for Image Emotion Distribution Learning," In Proceedings of ACM International Conference on Multimedia, 2023: 853 - 861.

H. Wang, X. Liu, P. Jing, and Y. Liu, “Airborne Ultrasound Haptics From Amplitude and Spatiotemporal Modulation of Acoustic Vortices,” IEEE Sensors Letters, 2023, 7(8): 1–4, Aug. 2023.

H. Wang, J. Tang, Z. Wu, and Y. Liu, “A Multibeam Steerable Parametric Array Loudspeaker for Distinct Audio Content Directing,” IEEE Sensors Journal, 2022, 22(13): 13640–13647.

Peiguang Jing, Yuechen Shang, Liqiang Nie, Yuting Su*, Jing Liu, Meng Wang. "Learning Low - rank Sparse Representations with Robust Relationship Inference for Image Memorability Prediction," IEEE Transactions on Multimedia, 2021, 23: 2259 - 2272.

Y. Wang, H. Wang, R. Liu, S. Wang, and Y. Liu, “A Hybrid Attention Network With Color Query for Image Colorization,” in 2025 44th Chinese Control Conference (CCC), Chongqing, China, July 2025.

Y. Lyu, H. Wang, K. Hu, S. Wang, and Y. Liu, “Text-aware learned image compression: Preserving text readability with mask-guided transform,” in 2025 44th Chinese Control Conference (CCC), 2025, pp. 8211–8216.

J. Tan, P. Jing, Y. Zhu, and Y. Liu, “MPBR: Multimodal progressive bidirectional reasoning for open-set fine-grained recognition,” in Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2025.

S. Wang, H. Wang, R. Liu, Z. Wu, B. Wei, and Y. Liu, “MSCFormer: Multi-Scale Circular Transformer for Image Deblurring,” in 2024 IEEE International Conference on Visual Communications and Image Processing (VCIP), 2024.

K. Hu, Y. Liu, F. Xu, R. Liu, H. Wang and S. Song, "Asymmetric Neural Image Compression with High - Preserving Information," 2024 IEEE International Symposium on Circuits and Systems (ISCAS), Singapore, Singapore, 2024, pp. 1 - 5, doi: 10.1109/ISCAS58744.2024.10558635.

Z. Huang, J. Duan, Y. Xie, and Y. Liu, “UDNet: Unified Deep Network Based on Transformer and Multi-Stage Fusion for Brain Tumor Classification from Undersampled MRI,” Neurocomputing, vol. 619, p. 129109, Feb. 2025.

Z. Huang, J. Duan, Y. Xie, and Y. Liu, “MAFDE-Net: Multipath Attention-Fusion-Based Dual-Encoder Network for Undersampled MRI Segmentation,” IEEE Transactions on Computational Imaging, vol. 11, pp. 1099–1114, 2025.

R. Liu, Y. Liu, H. Wang, J. Li, and K. Hu, “SAFFusion: A Saliency-Aware Frequency Fusion Network for Multimodal Medical Image Fusion,” Biomedical Optics Express, 2025, 16(6): 2459–2481.

P. Ding, J. Duan, H. Tao, and Y. Liu, “Enhanced Feature Contrastive Self-Supervised Learning Method Based on Deep Unfolding POCS for Accelerated Parallel MRI Reconstruction,” IEEE Transactions on Instrumentation and Measurement, 2025.

J. Duan, Z. Huang, Y. Xie, J. Wang, and Y. Liu, “Transformer- and Joint Learning-Based Dual-Domain Networks for Undersampled MRI Segmentation,” Medical Physics, 2024, 51(11): 8108–8123.

J. Duan, Y. Liu, and J. Wang, “Accelerated SPIRiT Parallel MR Image Reconstruction Based on Joint Sparsity and Sparsifying Transform Learning,” IEEE Transactions on Computational Imaging, 2023, 9: 276–288.

J. Duan, T. Pan, Y. Liu, and J. Wang, “Non-Local Low-Rank Constraint-Based Self-Consistent PMRI Reconstruction Using Eigenvector Maps,” IET Signal Processing, 2023, 17(3): e12180.

T. Pan, J. Duan, J. Wang, and Y. Liu, “Iterative Self-Consistent Parallel Magnetic Resonance Imaging Reconstruction Based on Nonlocal Low-Rank Regularization,” Magnetic Resonance Imaging, 2022, 88: 62–75.

R Liu, Y Liu, H Wang, K Hu, S Du. "A Novel Medical Image Fusion Framework Integrating Multi - scale Encoder - Decoder with Discrete Wavelet Decomposition," ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and ….

P. Cao, H. Wang, H. Cao, Z. Wu, and Y. Liu, “A Flexible Dual-Mode and Efficient RISC-V Coprocessor for On-Node FFT Acceleration in Edge Sensing,” IEEE Embedded Systems Letters, 2025, pp. 1–1.

Q. Yin, D. Li, Z. Wu, S. H. Pun, and Y. Liu, “Design and Implementation of RISC-V System-on-Chip for SPWM Generation Based on FPGA,” IEICE Electronics Express, 2024, 21(24): 20240603.

Chen Y, Dejian L, Xi F, Yu Liu, et al. "Fast Fourier transform convolutional neural network accelerator based on overlap addition," The Journal of China Universities of Posts and Telecommunications, 2024, 31(05): 71 - 84. DOI: 10.19682/j.cnki.1005 - 8885.2024.0015.

Yin, Xiaodi, Zhipeng Wu, Dejian Li, Chongfei Shen, and Yu Liu. "An efficient hardware accelerator for block sparse convolutional neural networks on fpga," IEEE Embedded Systems Letters, 2023.

J. Lai, L. Yang, D. Li, C. Shen, X. Feng, J. Wei, and Y. Liu, “Design and Optimization of Winograd Convolution on Array Accelerator,” Journal of Beijing Institute of Technology, 2023, 32(1): 69–81.

唐钏, 刘昱, 曾林. “面向步进电机控制的RISC-V微控制器的设计与实现,” 重庆大学学报, 2021, 44(11): 31–39.

W. Han, H. Wang, Z. Wu, and Y. Liu, “Design of a RISC-V based hybrid encryption coprocessor for resource-constrained environments,” in 2025 International Symposium of Electronics Design Automation (ISEDA), 2025, pp. 64–69.

T. Miao, Z. Wu, D. Li, Y. Lyu, M. I. Vai, and Y. Liu, "FCCQA: A high-performance FPGA-based accelerator for approximate nearest neighbor search," 2025 IEEE International Symposium on Circuits and Systems (ISCAS), 2025, pp. 1-5.

J. Zhang, N. Li, Z. Wu, and Y. Liu, “GAS: A flexible CNN accelerator architecture for heterogeneous dataflow implementation,” in 2025 International Symposium of Electronics Design Automation (ISEDA), 2025, pp. 52–57.

唐钏, 白志华, 李德建, 王于波, 刘昱. “面向SM4算法优化的指令集扩展方法与SoC实现,” 第十五届全国信号和智能信息处理与应用学术会议论文集, 2022, p. 107.

Z. Wu, H. Wang, N. Li, H. Cao, and Y. Liu, “HAOT: Heterogeneous Hardware-Aware Tensor Computation Optimization Framework via Transformer,” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2025, pp. 1–1.

H. Cao, Z. Wu, D. Li, P. Jing, S. H. Pun, and Y. Liu, “Accelerating control flow on CGRAs via speculative iteration execution,” IEEE Computer Architecture Letters, 2025.

Wu, Zhipeng, Yue Hu, Ning Li, Wei Lu, and Yu Liu. "HiEval: A scheduling performance estimation approach for spatial accelerators via hierarchical abstraction," Journal of Systems Architecture, 148 (2024): 103079.

Li, Ning, Dejian Li, Zhipeng Wu, Peiguang Jing, Sio Hang Pun, and Yu Liu. "SubMap: A Partial Mapping Strategy for CGRA Based on sub-CGRA Exploration," IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2024).

Z. Wu, Y. Liu, N. Li, H. Cao, and H. Wang, “An agile design method for reconfigurable spatial accelerators in tensor computation,” in 2025 International Symposium of Electronics Design Automation (ISEDA), 2025, pp. 35–40.

Hu, Yue, Chongfei Shen, Lixin Yang, Zhipeng Wu, and Yu Liu. "A novel predictor with optimized sampling method for hardware-aware NAS," In 2022 26th International Conference on Pattern Recognition (ICPR), pp. 2114 - 2120. IEEE, 2022.

F. Zuo, P. Jing, J. Sun, J. Duan, Y. Ji, and Y. Liu, “Deep Learning-Based Eye-Tracking Analysis for Diagnosis of Alzheimer’s Disease Using 3D Comprehensive Visual Stimuli,” IEEE Journal of Biomedical and Health Informatics, Feb. 2024.

Y. Yin, H. Wang, S. Liu, J. Sun, P. Jing, and Y. Liu, “Internet of Things for Diagnosis of Alzheimer’s Disease: A Multimodal Machine Learning Approach Based on Eye Movement Features,” IEEE Internet of Things Journal, 2023, 10(13): 11476–11485.

J. Sun, Y. Liu, H. Wu, P. Jing, and Y. Ji, “A Novel Deep Learning Approach for Diagnosing Alzheimer’s Disease Based on Eye-Tracking Data,” Frontiers in Human Neuroscience, 2022, 16: 972773.

J Sun, Z Wu, H Wang, P Jing, Y Liu. "A novel integrated eye - tracking system with stereo stimuli for 3 - D gaze estimation," IEEE Transactions on Instrumentation and Measurement 72, 1 - 15.

H. Jiang, J. Liu, H. Gu, Y. Wang, and Y. Liu, “Healthcare IoT-Enabled PMAFNet: A Progressive Multimodal Adaptive Fusion Network for Understanding HbA1c Fluctuations,” IEEE Internet of Things Journal, 2025, 12(23): 50427–50439.

H. Jiang, H. Wang, T. Pan, Y. Liu, P. Jing, and Y. Liu, “Mobile Application and Machine Learning-Driven Scheme for Intelligent Diabetes Progression Analysis and Management Using Multiple Risk Factors,” Bioengineering, 2024, 11(11): 1053.

Y Liu, S Li, H Jiang, J Wang. "Exploring the relationship between hypertension and nutritional ingredients intake with machine learning," Healthcare Technology Letters 7 (4), 103 - 108.

Y. Ru, H. Jiang, H. Song, B. Wei, and Y. Liu, “DDIN: Enhancing Food Ingredient Recognition with Region and Category Discovery Modules,” in 2024 IEEE International Conference on Visual Communications and Image Processing (VCIP), 2024.

Y Liu, Q Gong, S Wang, L Zhang, F Xu. "An Outdoor Pedestrian Localization Scheme Fusing PDR and VPR," Wireless Communications and Mobile Computing 2022 (1), 2898343.

Y Liu, S Li, C Mu, Y Wang. "Step length estimation based on D‐ZUPT for pedestrian dead‐reckoning system," Electronics letters 52 (11), 923 - 924.

L Zhang, Y Liu, J Sun. "A hybrid framework for mitigating heading drift for a wearable pedestrian navigation system through adaptive fusion of inertial and magnetic measurements," Applied Sciences 11 (4), 1902.

L Zhang, B Chen, H Li, Y Liu. "Deep neural network‐based adaptive zero‐velocity detection for pedestrian navigation system," Electronics Letters 58 (1), 28 - 31.

B Chen, R Zhang, S Wang, L Zhang, Y Liu. "Deep - learning - based inertial odometry for pedestrian tracking using attention mechanism and res2net module," IEEE Sensors Letters 6 (11), 1 - 4.

"Pedestrian dead reckoning" RUNNER-UP," IEEE IPIN 2017 Indoor Localization Offline Competition, in Sapporo 2017.

F. Xu, Z. Xie, K. Hu, Y. Liu, S. Song, T. A. Gulliver, Y. Xie, Y. Yang, and B. Duo, “Multi-antenna UAV assisted hybrid FSO/RF data collection for IoT: Optimal design for fairness,” IEEE Transactions on Aerospace and Electronic Systems, 2025.

D. Li, Z. Wang, H. Wang, S. H. Pun, P. U. Mak, A. Zhang, Y. Liu, H. C. Li, Y. Gao, et al., “Dynamic path gain compensation for enhancing intracardiac communication in leadless pacemakers,” IEEE Transactions on Instrumentation and Measurement, 2025.