Bio

Zhu Li (Bio, CV) is now a professor with the Dept of Computer Science & Electrical Engnieering (CSEE), University of Missouri,Kansas City, and the director of the NSF Center for Big Learning at UMKC . He was an AFRL summer visiting professor at the US Air Force Academy , Colorado Springs, Summer of 2016-18, 2020, and 2022. He received his PhD in Electrical & Computer Engineering from Northwestern University, Evanston in 2004. He was Sr. Staff Researcher/Sr. Manager with with Samsung Research America's Multimedia Standards Research Lab in Richardson, TX, 2012-2015, Sr. Staff Researcher/Media Analytics Group Lead with FutureWei (Huawei) Technology's Media Lab in Bridgewater, NJ, 2010~2012, and an Assistant Professor with the Dept of Computing, The Hong Kong Polytechnic University from 2008 to 2010, and a Principal Staff Research Engineer with the Multimedia Research Lab (MRL), Motorola Labs, from 2000 to 2008.

His research interests include image/video, light field and point cloud compression, deep learning based compression schemes, image/video denoising and super-resolution, video hashing and identification, as well as the video communication system issues like joint source-channel coding, rate-distortion optimization and communication resource management. He has 46 issued or pending patents, 100+ publications in book chapters, journals, conference proceedings and standard contributions in these areas. He is an IEEE senior member, Associate Editor-in-Chief (AEiC) for IEEE Trans on Circuits & System for Video Technology, Associate Editor (2020~) for IEEE Trans on Image Processing , associated editor for IEEE Trans.on Multimedia, 2016-19,for IEEE Trans on Circuits & System for Video Technology, 2015-18, for Journal of Signal Processing Systems (Springer), 2015~present, steering committee memeber of IEEE ICME, elected member (2014-2017) of the IEEE Multimedia Signal Processing (MMSP) Tech Committee, elected Vice Chair (2008-2010), Standards Liaison (2014-2016) of the IEEE Multimedia Communication Technical Committee (MMTC), member of the Best Paper Award Committee, ICME 2010, co-editor for the Springer-Verlag book on "Intelligent Video Communication: Techniques and Applications", and " Multimedia Analysis, Computing and Communication,". He received the Best Poster Paper Award at IEEE Int'l Conf on Multimedia & Expo (ICME), Toronto, 2006, and the Best Paper (DoCoMo Labs Innovative Paper) Award at IEEE Int'l Conf on Image Processing (ICIP), San Antonio, 2007.

Recent papers can be found at here

Teaching

  • Spring 2023: ECE/CS 5582 Computer Vision , previous offerings: 2022 Fall
  • Fall 2022: ECE/CS 5578 Multimedia Communication , previous offerings: 2020
  • Fall 2019: ECE/CS 484 Digital Image Processing
  • Fall 2017: Adv. Multimedia Communication

    Invited Talks

    - Mobile Visual Search: Object Re-Identification Against Large Repositories, invited talk at Academia Sinica, Taipei, 2015.12, hosted by Prof. Wen-Huang Cheng, University of Science & Tech of China (USTC), hosted by Prof. Houqiang Li, and Shanghai Jiaotong University, hosted by Prof. Y.L. Xu, 2016.01.
    - Subspace Indexing on Grassmannian Manifold for Large Scale Visual Identification, given at EPFL/IBM Research/Northwestern Univ/Stevens Tech/Motorola Solutions Research/MIT Lincoln Lab/Beijing University.

  • Multimedia Computing & Communication Lab

    Publications:

    People:

    • Yangfan Sun, MS UMKC, PhD Student (Spring 2017~), Light field compression and super resolution.
    • Raghunath Puttagunta, MS UMKC, PhD Student (Fall 2017~) , Hyper Spectral Imaging.
    • Birendra Kathariya, MS UMKC, PhD Student (Fall, 2017~), Point Cloud Compression
    • Paras Maharjan, MS/PhD student, Deep learning image enhancement/post processing. 2018~
    • Matthew Kayrish, PhD Student (Spring, 2019~).
    • Rijun Liao, PhD Student (Spring 2020~), B.S & M.S, Shenzhen University, Computer Vision, Biometrics.
    • Chris Henry, PhD Student (Fall'21 ~), B.S Hardmard Univ, M.S, Gachon Univ.
    • Sajid Umair, PhD Student (Fall'22 ~),
    • Zach Button, PhD Student (Fall'22 ~),
    • Muhamud Talha, PhD Student (Spring'23 ~),

    Alumni:

    • Anique Akhatar, PhD, 2022. Joined Qualcomm Video Codec Research team in San Diego.
    • Wei Jia, B.S and M.S, (Beijing Univ of Post & Telecomm)BUPT, PhD Student (Fall, 2018~21), Deep learning in compression, video transport.Now joining KWAI's video research team in San Diego, congrats !
    • Dewan F. Noor, Bangeladesh Univ of Engineering & Tech, PhD Student (Spring, 2016~2021), Gradient image super resolution, multi-frame super resolution. Now joined Tuskegee University as Asst Prof, congrats !
    • Li Li, PhD, Univ of Science & Tech of China, Visiting Assistant Professor/Asst. Director of MCC Lab (Fall, 2016~2020), Image/Video/Light Field/Point Cloud Compression. Now Associate Prof. with Univ of Science & Tech of China, congrats !
    • Zhaobin Zhang, Huazhong Univ of Science & Tech, PhD Student (Fall, 2016~20), Compression for machine. PhD, 2020, joining ByteDance Video Codec team in San Diego, Congrats !
    • Renlong Hang,Post-Doc Researcher (2018~2019), Asst. Prof., Nanjing Univ of Info Science & Tech (NUISCT).
    • Yixin Mei , visiting PhD student on CSC scholarship, Xian Jiaotong Univ (XJTU), 2019~2020, Compression for Machine Vision.
    • Han Zhang , visiting PhD student on CSC scholarship, Shanghai Jiaotong Univ (SJTU), 2018~2019.
    • Yang Zhou, visiting faculty from Hanghzou Dianzi University, 2018.08-2019.08.
    • Wenjie Zhu , visiting PhD student on CSC scholarship, Shanghai Jiaotong Univ (SJTU), 2017~2018.
    • Yue Li , visiting PhD student on CSC scholarship, Univ of Science & Tech of China (USTC), 2017.09-2018.09.
    • Karthik Ainala, MS Thesis ( Low Latency Point Cloud Compression and Communication ) Student (graduated, 2018)
    • Eric Cornwell , MS Thesis (Dense Camera Capture Light Field Compression ) Student (graduated 2017, now with Honeywell KCP)
    • Prasana Gadiparthi, MS Thesis (Content De-Duplication with Spatio-Temporal Compact Hash) Student (graduated 2017, now with American Express)
    • Shaina Krumme, RA/visiting student, Univ of Kansas (Summer 2017, 18).
    • Gerry Xie, undergrad research student, Dept of ECE, Univ of California, San Diego.
    • Shelby Mohar, undergrad research student, Dept of CSEE, UMKC, working on the NEH project of hyperspectral imaging of ancient scriptures, 2021.01-2021.05.
    • Caleb van Tassel research assitant, NSF-AFRL project on remote sensing and joint pixel-frequency domain attention network in areial image classification. 2021.08-2022.05.
    • Haley Griffin research assistant, NSF AFRL project on remote sensing, 2022.03~2022.08
    • Siqi Wu, undergrad research student, Dept of Statistics, Univ of Kansas. now PhD student at Missouri, Columbia.

    Research Projects:

    • Depth sensing and Point Cloud Capture and Comperssion for auto-driving and 3D mapping (PCC)
    • Future Video Codec with deep learning for compression (FVC)
    • Deep Learning Model Compression and Acceleration (DLMCA)
    • Low Resolution and Quality Image Enhancement and Recognition (LRQIER)
    • Multimedia Transport System research, Low latency visual communication, immersive visual communication system (MMSys)

    Sponsors:

    Many thanks to the generous support from: Sponsors
    Full publication list
    In review
    1. D. Noor, Z. Li, S. Bhattacharyya, and G. York, "See SIT in Dark: Cascade Network for Learning DoG Pyramid in Dark", in review with ACM Trans on Multimedia Computing, Communication, and Applications, (TOMM), 2021.
    2. Y. Sun, S. Wang, L. Li, Z. Li, and G. Li, "Learn a Compact Spatial-Angular Representation for Light Field", in review with Int'l Journal on Computer Vision (IJCV), 2021.
    3. J. Wang, D. Ding, Z. Li, X. Feng, C. Cao, and Z. Ma, "Sparse Tensor-based Multiscale Representation for Point Cloud Geometry Compression", in review with IEEE Trans on PAMI, 2021.
    2022
    1. J. Wang, D. Ding, Z. Li, X. Feng, C. Cao and Z. Ma, "Sparse Tensor-based Multiscale Representation for Point Cloud Geometry Compression", accepted, IEEE Trans. on Pattern Analysis & Machine Intelligence(T-PAMI), 2022.
    2. Y. Sun, L. Li, Z. Li, S. Wang, S. Liu and G. Li, "Learning a Compact Spatial-Angular Representation for Light Field", IEEE Trans. on Multimedia(T-MM), 2022.
    3. Y. Sun, Z. Li, S. Wang, and W. Gao, “Learning-based Depth-Guided Light Field Factorization for Compressive Light Field Display”, Optical Express, 2022.
    4. B. Chen, L. Zhu, C. Kong, H. Zhu, S. Wang, and Z. Li, "No-Reference Image Quality Assessment by Hallucinating Pristine Features", IEEE Trans. on Image Processing(T-IP), 2022.
    5. Y. Wen; B. Liu; J. Cao; R. Xie; L. Song; Z. Li, "IdentityMask: Deep Motion Flow Guided Reversible Face Video De-identification", to appear, IEEE Trans. on Circuits & Sys. for Video Tech., 2022.
    6. R. Liao, Z. Li, S. Bhattacharyya, and G. York, "PoseMapGait: A Gait Recognition Method based on Evolution of Pose Estimation Maps and GraphConvolutional Network", accepted, Neurocomputing, 2022.
    7. L. Li, Z. Li, S. Liu, and H. Li, "Frame-level Rate Control for Geometry-based LiDAR Point Cloud Compression", accepted, IEEE Trans. on Multimedia, 2022.
    8. A. AKhtar, Z. Li, G. V. Auwera, L. Li, and J. Chen, "PU-Dense: Sparse Tensor-based Point Cloud Geometry Upsampling", accepted, IEEE Trans. on Image Processing, 2022.
    9. L. Li, Z. Li, S. Liu and H. Li, "Plenoptic Point Cloud Compression Using Multiview Extension of High Efficiency Video Coding," in IEEE Trans. on Multimedia, doi: 10.1109/TMM.2022.3142528.
    10. Z. Liu, F. Li, Z. Li, and B. Luo, "LoneNeuron: a Highly-effective Feature-domain Neural Trojan using Invisible and Polymorphic Watermarks ", ACM Conference on Computer and Communications Security(CSS), 2022.
    11. Z. Liu, F. Li, J. Lin, Z. Li, and B. Luo. Hide and Seek: on the Stealthiness of Attacks against Deep Learning Systems. In European Symposium on Research in Computer Security (ESORICS), 2022.
    12. A. Akhtar, Z. Li, G. Auwera, J. Chen, "Dynamic Point Cloud Interpolation", in IEEE Int'l Conf on Audio, Speech and Signal Processing (ICASSP), 2022.
    13. Y. Sun, Z. Li, L. Li, S. Wang, and W. Gao, "Optimization of compressive light field display in dual-guided learning", in IEEE Int'l Conf on Audio, Speech and Signal Processing (ICASSP), 2022.
    14. S. Huang, H. Chang, W. Wu, and Z. Li, "DPGIR: SIFT Recovery from a Hazy Image", IEEE Int'l Conf on Multimedia & Expo(ICME), Taipei, 2022.
    15. W.Wu, H. Chang, Y. Zheng, Z. Li, Z. Chen, and Z. Zhang, "Contrastive Learning-based Robust Object Detection under Smoky Conditions", IEEE CVPR Workshop, New Orleans, 2022.
    16. T. Fan, L. Gao, Y. Xu , Z. Li and D. Wang, "D-DPCC: Deep Dynamic Point Cloud Compression via 3D Motion Prediction", Proc of IJCAI, 2022.
    17. H. Jiang, P. Maharjan, Z. Li and G. York, "DCT-based Residual Network for NIR Image Colorization", IEEE Intl Conf on Image Processing (ICIP), Bordeaux, France, 2022.
    18. C. Henry, B. Kathariya, M. S. Asif, Z. Li, and G. York, "Aerial Image Classification through Thin Lenseless Camera", Int'l Conf on Multimedia Information Processing and Retrieval (MIPR), 2022.
    19. L. Hou, L. Gao, Y. Xu, Z. Li, X. Xu and S. Liu, "Learning-based Intra-Prediction For Point Cloud Attribute Transform Coding", IEEE Workshop on Multimedia Signal Processing (MMSP), Shanghai, China, 2022.
    20. B. Kathariya, Z. Li, H. Wang, Geert Van Der Auwera, "Multi-stage Locally and Long-range Correlated Feature Fusion for Learned In-loop Filter in VVC", IEEE International Conference on Visual Communications and Image Processing (VCIP), Suzhou, China, 2022.
    21. B. Kathariya, Z. Li, H. Wang, and M. Coban, "MULTI-STAGE SPATIAL AND FREQUENCY FEATURE FUSION USING TRANSFORMER IN CNN-BASED IN-LOOP FILTER FOR VVC", Picture Coding Symposium (PCS), San Jose, 2022.
    2021
    1. Z. Li, S. Liu, F. Dufaux, L. Li, G. Li and C. . -C. J. Kuo, "Guest Editorial Introduction to the Special Issue on Recent Advances in Point Cloud Processing and Compression," in IEEE Transactions on Circuits and Systems for Video Technology(T-CSVT), vol. 31, no. 12, pp. 4555-4560, Dec. 2021, doi: 10.1109/TCSVT.2021.3129071.
    2. D. Yang, Y.-X Zou, Z. Li and G. Li, “Learning Human-Object Interaction via Interactive Semantic Reasoning”, IEEE Trans on Image Processing(T-IP), 2021. doi: 10.1109/TIP.2021.3125258
    3. L.Li, Z. Li, S. Liu and H. Li, "Motion Estimation and Coding Structure for Inter-prediction of LiDAR Point Cloud Geometry", accepted, IEEE Trans on Multimedia (T-MM), 2021.
    4. Y. Mei, L. Li, Z. Li, and F. Li, "Learning-Based Scalable Image Compression with Latent-Feature Reuse and Prediction", IEEE Trans on Multimedia (T-MM), 2021.
    5. R. Hang, Q. Liu, and Z. Li, "Spectral Super-Resolution Network Guided by Intrinsic Properties of Hyperspectral Imagery", IEEE Trans on Image Processing(T-IP), doi:10.1109/TIP.2021.3104177, 2021.
    6. W. Jia, L.Li, Z. Li, and S. Liu, "Deep Learning Geometry Compression Artifacts Revomal for Video Based Point Cloud Compression", accepted, Int'l Journal on Computer Vision (IJCV), 2021.
    7. A. Akhtar, W.Gao, L. Li, Z. Li, W. Jia, and S. Liu, "Video-based Point Cloud Compression Artifact Removal", accepted, accepted, IEEE Trans on Multimedia (T-MM), 2021.
    8. W. Ji, T. Ebrahimi, Z. Li, J. Yuan, D. Wu, Y. Xin, "Guest Editorial: Emerging Visual IoT Technologies for Future Communications and Networks", IEEE Wireless Comm. , vol. 28(4): 10-11 (2021)
    9. W. Jia, L. Li, Z. Li and S. Liu, "Convolutional Neural Network-based Occupancy Map Accuracy Improvement for Video-based Point Cloud Compression", accepted, IEEE Trans on Multimedia (T-MM), 2021.
    10. X. Sheng, L. Li, D. Liu, Z. Xiong, Z. Li, and F. Wu, "Deep-PCAC: An End-to-End Deep Lossy Compression Framework for Point Cloud Attributes", accepted, IEEE Trans on Multimedia (T-MM), 2021.
    11. R. Liao, W. An, Z. Li, and S. S. Bhattacharyya, "A novel view synthesis approach based on view spacecovering for Gait Recognition", Neurocomputing , 2021.
    12. W. Jia, L. Li, Z. Li, X. Zhang and S. Liu, “Residual-Guided In-Loop Filter Using Convolution Neural Network”, accepted, ACM Trans on Multimedia Computing, Communication and Applications (TOMM), 2021.
    13. T. Li, K. Zhang, S. Shen, B. Liu, Q. Liu, Z. Li"Image Co-saliency Detection and InstanceCo-segmentation using Attention Graph Clusteringbased Graph Convolutional Network" IEEE Trans on Multimedia(TMM), 2021.
    14. J. Wang, D. Ding, Z. Li, and Z. Ma, "Multiscale Point Cloud Geometry Compression", IEEE Data Compression Conference(DCC), Snowbird, USA, 2021.
    15. Md A. Arefeen, S. T. Nimi, Md Y. Uddin, and Z. Li, "A Lightweight ReLU-Based Feature Fusion for Aerial Scene Classification", IEEE Int'l Conf on Image Processing (ICIP), Alaska, USA, 2021.
    16. P. Wang, W. Wu, Z. Li, and Y. Liu, "See SIFT in a Rain: Divide-and-conquer SIFT Key Point Recovery from a Single Rainy Image", IEEE Visual Comm & Image Processing (VCIP) Conf , München, Germany, 2021.
    17. Y. Mei, F. Li, L. Li and Z. Li, "Learn A Compression for Objection Detection - VAE with a Bridge", IEEE Visual Comm & Image Processing (VCIP) Conf , München, Germany, 2021.
    18. R. Liao, Z. Li, S. Bhattacharyya, and G. York, "Aerial Image Classification with Label Splitting and Optimized Triplet Loss Learning", IEEE Visual Comm & Image Processing (VCIP) Conf , München, Germany, 2021.
    19. P. Maharjan, N. Xu, X. Xu, and Z. Li, "DCTResNet: Transform Domain Image Deblocking for Motion Blur Images", IEEE Visual Comm & Image Processing (VCIP) Conf , München, Germany, 2021.
    20. B. Kathariya, Z. Li, J. Chen, and G. Aweera, "Gradient Compression with a Variational Coding Scheme for Federated Learning", IEEE Visual Comm & Image Processing (VCIP) Conf , München, Germany, 2021.
    21. G. Xie, Z. Li, A. Mehmood, S. Bhattacharyya, "Plug-and-Play Deblurring for Robust Object Detection", IEEE Visual Comm & Image Processing (VCIP) Conf , München, Germany, 2021.
    2020
    1. Q. Yang, Z. Ma, Y. Xu, Z. Li, and J. Sun, “GraphSIM - Inferring Point Cloud Quality via Graph Similarity”, to appear, IEEE Trans on Pattern Analysis & Machine Intelligence (T-PAMI), 2020.
    2. Y. Li, Y. Yi, D. Liu, L. Li, Z. Li, and H. Li, “Neural Network Based Cross-Channel Intra Prediction”, ACM Trans on Multimedia Computing Communication and Applications (TOMM), 2020.
    3. L. Li, Z. Li, S. Liu, H. Li, "Efficient Projected Frame Padding for Video-based Point Cloud Compression", accepted, IEEE Transactions on Multimedia(T-MM).
    4. H. Zhang, L. Song, L. Li, Z. Li, and X.K. Yang, “Compression Priors Assisted Convolutional Neural Network for Fractional Interpolation”, accepted, IEEE Transactions on Circuits and Systems for Video Tech. (T-CSVT).
    5. R. Hang, Z. Li, Q. Liu, P. Ghamisi and S. Bhattacharyya, "Hyperspectral Image Classification with Attention Aided CNNs", accepted, IEEE Trans. on Geoscience & Remote Sensing (T-GRS), 2020.
    6. L. Li, Z, Li, S. Liu, H. Li, "Rate Control for Video-based Point Cloud Compression", accepted, IEEE Transactions on Image Processing(T-IP).
    7. W. Zhu, Z. Ma, Y. Xu, L. Li, and Z. Li, “View-Dependent Dynamic Point Cloud Compression”, accepted, IEEE Transactions on Circuits and Systems for Video Technology(T-CSVT), 2020.
    8. Z. Zhang, X. Zhao, X. Li, L. Li, S. Liu, and Z. Li "Fast DST-7/DCT-8 with Dual Implementation Support for Versatile Video Coding", accepted IEEE Trans on Circuits & Sys. for Video Tech. (T-CSVT).
    9. R. Hang, Z. Li, P. Ghamisi, D. Hong, G. Xia and Q. Liu, "Classification of Hyperspectral and LiDAR DataUsing Coupled CNNs", accepted, IEEE Trans. on Geoscience & Remote Sensing (TGRS).
    10. R. Puttagunta, R. Hang, Z. Li, S. Bhattacharyya, and G. York, "Spectral Super Resolution with DCT Decomposition and Deep Residual Learing", Int'l Conf on Dynamic Data Driven Application Systems(DDDAS), 2020.
    11. L. Li, Z. Li, S. Liu, H. Li, "Occupancy-map-based Rate Distortion Optimization and Partition for Video-based Point Cloud Compression", accepted, IEEE Transactions on Circuits and Systems for Video Technology (T-CSVT).
    12. Li Li, N. Yan, Z. Li, S. Liu, H. Li, "λ-domain Perceptual Rate Control for 360-degree Video Compression", accepted, IEEE Journal of Selected Topics in Signal Processing (JSTSP).
    13. W. Jia, L. Li, Z. Li, S. Zhao and S. Liu, Scalable Hash From Triplet Loss Feature Aggregation for Video De-Duplication, Journal of Visual Communication & Image Representation (JVCIR), 2020.
    14. K. Zhang, L. Wang, D. Liu, B. Liu, Q. Liu and Z. Li, "Dual Temporal Memory Network for Efficient Video Object Segmentation", ACM Multimedia (MM), Seattle, 2020.
    15. Y. Sun, L. Li, Z. Li, and S. Liu, "Referenceless Rate-Distortion Modeling with Learning from Bitstream and Pixel Features", ACM Multimedia (MM), Seattle, 2020.
    16. Y. Mei, F. Li, L. Li, and Z. Li, "Activation Map Saliency Guided Filtering for Efficient Image Compresison for Vision Tasks", IEEE Asilomar Conference on Signals, Systems and Computers, Monterey, 2020.
    17. B. Kathariya, L. Li, Z. Li, L. Duan, and S. Liu, "Network Update Compression for Federated Learning", IEEE Visual Communication & Image Processing Conf (VCIP), Hong Kong, 2020.
    18. A. Akhtar, W. Gao, L. Li, Z. Li, X. Zhang, and S. Liu, "Point Cloud Geometry Prediction Across Spatial Scale using Deep Learning", IEEE Visual Communication & Image Processing Conf (VCIP), Hong Kong, 2020.
    19. R. Liao, W. An, S. Yu, Z. Li, and Y. Huang, "Dense-View GEIs Set: View Space Covering for Gait Recognitionbased on Dense-View GAN", Proc of Int'l Joint Conf on Biometrics (IJCB), 2020.
    20. L. Pan, F. Christophe, T. Mikkonen, Z. Li, and S. S. Bhattacharyya. Simulating Spiking Neural Networks with Timed Dataflow Graphs. In Proceedings of the Conference on Artificial Intelligence Circuits and Systems (AICAS), Genoa, Italy, March 2020.
    21. L. Li, Z. Li, S. Liu, and H. Li, "Video-based Compression for Plenoptic Point Clouds", IEEE Data Compression Conf (DCC), 2020.
    22. W. Jia, L. Li, Z. Li, S. Zhao, S. Liu, "Triplet Loss Feature Aggregation for Scalable Hash", IEEE Int'l Conf on Audio, Speech and Signal Processing (ICASSP), Barcelona, 2020.
    23. R. Hang, Z. Li, Q. Liu, and S. S. Bhattacharyya, “PRINET: A Prior Driven Spectral Super-Resolution Network”, IEEE International Conf on Multimedia & Expo (ICME), London, 2020.
    24. Y. Sun, L. Li. Z. Li, and S. Liu, “YOCO: Light-Weigth Rate Control Model Learning”, IEEE Int’l Conference on Image Processing (ICIP), Abu Dhabi, 2020.
    25. W. Jia, L. Li, Z. Li, X. Zhang and S. Liu, “Residual Guided Deblocking with Deep Learning”, IEEE Int’l Conference on Image Processing (ICIP), Abu Dhabi, 2020.
    2019
    1. Li Li, Zhu Li, Vladyslav Zakharchenko, Jianle Chen, Houqiang Li, "Advanced 3D Motion Prediction for Video Based Dynamci Point Cloud Compression", accepted, IEEE Trans on Image Processing(T-IP), 2019.
    2. W. Ji, Z. Li, H.V. Poor, W. Zhu, and C. Timmerer, “Guest Editorial: Multimedia Economics for Future Networks:Theory, Methods, and Applications”, IEEE Journal on Selected Areas in Communication(J-SAC), 2019.
    3. L. Li, Z. Li, B. Li, D. Liu, H. Li, "Quadtree-based Coding Framework for High Density Camera Array based Light Field Image", IEEE Trans on Circuits and Systems for Video Technology(T-CSVT), 2019.
    4. D. F. Noor, Y. Li, Z. Li, S. Bhattacharyya, and G. York, "Multi-scale gradient image super-resolution for preserving SIFT key points in low-resolution images", Signal Processing: Image Communication , 2019.
    5. S. Schwarz, M. Preda, V. Baroncini, M. Budagavi, P. César, P. A. Chou, R. A. Cohen, M. Krivokuca, S. Lasserre, Z. Li, J. Llach, K. Mammou, R. Mekuria, O. Nakagami, E. Siahaan, A. J. Tabatabai, A. M. Tourapis, V. Zakharchenko: Emerging MPEG Standards for Point Cloud Compression IEEE J. Emerg. Sel. Topics Circuits Syst(JESTCAS). 9(1): 133-148 (2019)
    6. J. Feng, C.K. Jung, and Z. Li, "Gradient Guided Image Deblocking Using Convolutional Neural Networks", Proc of ACM Multimedia Asia, 2019.
    7. Y. Sun, R. Hang, Z. Li, M. Jin, and K. Xu, "Privacy-Preserving Fall Detection with Deep Learning on mmWave Radar Signal", IEEE Visual Comm & Image Processing (VCIP), Sydney, 2019.
    8. R. Puttagunta, R. Hang, Z. Li, and S. Bhattacharyya, "Low Resolution Recognition of Aerial Images", IEEE Visual Comm & Image Processing (VCIP), Sydney, 2019.
    9. Y. Zhou, W. Yu, Z. Li, and H. Yin, "Stereoscopic Visual Discomfort Prediction Using Multi-scale DCT Features", ACM Multimedia , Nice, France, 2019.
    10. L. Li, Z. Li, S. Liu, H. Li, "Occupancy-map-based rate distortion optimization for video-based point cloud compression", IEEE Int'l Conf on Image Processing (ICIP), 2019.
    11. A. Akhtar, B. Kathariya, Z. Li, "Low Latency Scalable Point Cloud Communication", IEEE Int'l Conf on Image Processing (ICIP), 2019.
    12. H. Zhang, L. Li, L. Song, X.-K. Yang, Z. Li "Advanced CNN Based Motion Compensation Fractional Interpolation", IEEE Int'l Conf on Image Processing (ICIP), 2019.
    13. D. F. Noor, L. Li, Z. Li, S. Bhattacharyya, "Multi-Frame Super Resolution with Deep Residual Learning on Flow Registered Non-Integer Pixel Images", IEEE Int'l Conf on Image Processing (ICIP), 2019.
    14. P. Maharjan, L. Li, Z. Li, N. Xu, C. Ma, and Y. Li, "Improving Extreme Low-Light Image Denoising via Residual Learning", IEEE Int'l Conf on Multimedia & Expo (ICME), Shanghai, 2019.
    15. A. Akhtar, J. Ma, R. Shafin, J. Bai, L. Li, Z. Li, and L. Liu, "Low Latency Scalable Point Cloud Communication in VANETs using V2I Communication", IEEE Int'l Conf on Communication (ICC), Shanghai, 2019.
    16. L. Li, Z. Li, V. Zakharchenko, and J. Chen, "Advanced 3D Motion Prediction for Video Based Point Cloud Attributes Compression", IEEE Data Compression Conf (DCC), Snowbird, USA, 2019.
    17. Z. Zhang, X. Zhao, X. Li, Z. Li, and S. Liu, "Fast Adaptive Multiple Transform for Versatile Video Coding", IEEE Data Compression Conf (DCC), Snowbird, USA, 2019.
    18. B. Kathariya, V. Zakharchenko, Z. Li, and J. Chen, "Level-of-detail generation using binary-tree for lifting scheme in LiDAR point cloud attributes coding" IEEE Data Compression Conf (DCC), Snowbird, USA, 2019.
    19. L. Li, Z. Li, Y. Li, B. Kathariya, and S. Battacharyya, "Incremental Deep Neural Network Pruning based on Hessian Approximation" IEEE Data Compression Conf (DCC), Snowbird, USA, 2019.
    20. D. F. Noor, Y. Li, Z. Li, S. Bhattacharyya, G. York, "Gradient Image Super-Resolution for Low Resolution Image Recognition", IEEE Int'l Conf on Acoustics, Speech and Signal Processing (ICASSP), Brighton, UK, 2019.
    21. Z. Zhang, Y. Li, L. Li, Z. Li, S. Liu, "Multiple Linear Regression for High Efficiency Video Intra Coding", IEEE Int'l Conf on Acoustics, Speech and Signal Processing (ICASSP), Brighton, UK, 2019.
    22. Y. Xu, W. Zhu, Y. Xu, Z. Li, "Dynamic Point Cloud Geometry Compression via Patch-wise Polynomial Fitting", IEEE Int'l Conf on Acoustics, Speech and Signal Processing (ICASSP), Brighton, UK, 2019.
    2018
    1. Z. Zhang, L. Li, Z. Li, and H. Li, "Mobile Visual Search Compression with Grassmann Manifold Embedding", IEEE Trans on Circuits & Sys for Video Tech , accepted.
    2. Y. Li and Z. Li, "Light Field Compression", book chapter in Springer-Verlag Book in Dynamic Data Driven Applications Systems (DDDAS)", Ed. Erik Blausch, to appear, 2018.
    3. Y. Li, L. Li, D. Li, H. Li, Z. Li, and F. Wu, “Learning a Convolutional Neural Network for Image Compact Resolution”, accepted, IEEE Trans on Image Processing , 2018.
    4. Li Li, Zhu Li, Xiang Ma, Haitao Yang and Houqiang Li, "Advanced Spherical Motion Model and Local Padding for 360 Video Compression", accepted in IEEE Transactions on Image Processing vol. 28, no. 5, pp. 2342-2356, May 2019.
    5. B. Kathariya, L. Li, Z. Li, and J. Alvarez, “Lossless Dynamic Point Cloud Geometry Compression with Inter Compensation and Traveling Salesman Prediction”, IEEE Data Compression Conference (DCC) , Snow Bird, 2018.
    6. S. Zhao, G. Muppala, Z. Li, D. Medhi, "Smooth Streaming With MPEG-DASH Using SDN-Based Application-Aware Networking". Intl Conf on Computing, Networking and Communications (ICNC)2018: 77-81
    7. N. Reddy, D. Noor, Z. Li, and R. Derakhashani, “Multi-Frame Super Resolution Occular Biometrics”, IEEE Computer Society Biometrics Workshop (CVPRW on Biometrics) , Salt Lake City, USA, 2018.
    8. Duc Huy Hoang Nguyen, R. Puttagunta, Z. Li, and R. Derakhshani, "User Re-Identification Using Clothing Information for Smartphones", IEEE Int'l Symposium on Technologies for Homeland Security , Woburn, MA, 2018. Best Paper Award
    9. B. Kathariya, L. Li, Z. Li, and J. Alvarez, “Scalable Point Cloud Geometry Coding with Binary Tree Embedded Quadtree”, IEEE Int'l Conf. on Multimedia & Expo (ICME) ,San Diego, USA, 2018.
    10. Y. Shao, Q. Zhang, G. Li and Z. Li, "Hybrid Point Cloud Attribute Compression Using Slice-based Layered Structure and Block-based Intra Prediction" ACM Multimedia , Seoul, Korea, 2018.
    11. Y. Li, L. Li, Z. Li, J. Yang, N. Xu, D. Liu, H. Li, "A Hybrid Neural Network for Chroma Intra Prediction" IEEE Int'l Conf on Image Processing (ICIP), Athens, Greece, 2018.
    12. Y. Sun, M. J. L. Li, and Z. Li, "A Machine Learning Approach to Accurate Sequence Level Rate Control Scheme for Video Coding" IEEE Int'l Conf on Image Processing (ICIP), Athens, Greece, 2018.
    13. Xin Zhao, Li Li, Zhu Li, Xiang Li, Shan Liu, "Coupled Primary and Secondary Transform for Next Generation Video Coding", IEEE Visual Communication & Image Processing Conf (VCIP), Taiwan, 2018.
    14. Zhuoqun Wang, Zhu Li, Yiling Xu, Jun Sun, "Selective Convolutional Features based Generalized-mean Pooling for Fine-grained Image Retrieval" IEEE Visual Communication & Image Processing Conf (VCIP), Taiwan, 2018.
    15. Zhaobin Zhang, Yue Li, Li Li, Li Zhu, Shan Liu, "Combining Intra Block Copy and Neighboring Samples Using Convolutional Neural Network for Image Coding" IEEE Visual Communication & Image Processing Conf (VCIP), Taiwan, 2018.
    2017
    1. L. Li, Z. Li, B. Li, D. Liu, and H. Li, “Pseudo sequence based 2-D hierarchical coding structure for light-field image compression”, to appear, IEEE Journal of Selected Topics in Signal Processing , Special Issue on Light Field, 2017.
    2. L. Li, H. Li, D. Liu, Z. Li, H. Yang, S. Lin, F. Wu, “An Efficient Four-Parameter Affine Motion Model for Video Coding”, to appear, IEEE Trans on Circuits & System for Video Tech , 2017.
    3. S. Zhao, Z. Li, D. Medhi, P. Lai, and S. Liu, "Study of User QoE Improvement for Dynamic Adaptive Streaming over HTTP (MPEG-DASH)", Intl Conf on Computing, Networking and Communications (ICNC), Santa Clara, 2017.
    4. L. Li, Z. Li, B. Li, D. Liu, and H.-Q. Li, "Pseudo Sequence based 2-D hierarchical reference structure for Light-Field Image Compression", IEEE Data Compression Conference (DCC), Snow Bird, 2017.
    5. Bowen Cheng, Zhangyang Wang, Zhaobin Zhang, Zhu Li, Ding Liu, Jianchao Yang, Shuai Huang, Thomas S Huang, "Robust emotion recognition from low quality and low bit rate video: A deep learning approach", 7th International Conference on Affective Computing and Intelligent Interaction (ACII), 2017.
    6. S. Feng, Z. Li, Y. Xu, and J. Sun, “Compact Scalable Hash from Deep Learning Features Aggregation for Content De-duplication”, IEEE Multimedia Signal Processing Workshop (MMSP), London, 2017.
    7. W. Zhu, L. Li, Z. Li and Y. Xu, “Lossless Point Cloud Geometry Compression via Binary Tree Partition and Intra Prediction”, IEEE Multimedia Signal Processing Workshop (MMSP), London, 2017.
    8. E. Cornwell, L. Li, Z. Li, and Y. Sun, “An Efficient Compression Scheme for the Multi-Camera Light Field Images”, IEEE Multimedia Signal Processing Workshop (MMSP), London, 2017.
    9. Z. Zhang, L. Li, Z. Li, and H. Li, “Visual Query Compression with Locality Preserving Projection on Grassmann Manifold”, IEEE Intl Conf on Image Processing (ICIP), Beijing, 2017.
    10. L. Li, Z. Li, M. Bugadavi, and H. Li, “PROJECTION BASED ADVANCED MOTION MODEL FOR CUBIC MAPPING FOR 360-DEGREE VIDEO”, IEEE Intl Conf on Image Processing (ICIP), Beijing, 2017.
    11. Y. Li, L. Li, Z. Li, and H. Li, “Hierarchical Piece-Wise Canonical Correlation Analysis Projections for Efficient Intra-Prediction Coding”, IEEE Visual Communication & Image Processing (VCIP) Conf, St. Petersberg, FL, 2017.
    12. Y. Shao, Z. Zhang, Z. Li, and G. Li, “Attribute Compression of 3D Point Clouds Using Laplacian Sparsity Optimized Graph Transform”, IEEE Visual Communication & Image Processing (VCIP) Conf, St. Petersberg, FL, 2017.
    13. B. Kathariya, K. Ainala, Z. Li, and R. Joshi, “">Embedded Binary Tree For Dynamic Point Cloud Geometry Compression with Graph Signal Resampling and Prediction”, IEEE Visual Communication & Image Processing (VCIP) Conf, St. Petersberg, FL, 2017.
      
    2016
      
    1. K. Aninala, R. Mekuria, B. Kathariya, Z. Li, Y.-K. Wang and R. Joshi, "An improved enhancement layer for octree based point cloud compression with plane projection approximation", SPIE App. of Digital Image Processing San Diego, 2016.
    2. W. Huang, Y.-L. Xu, and Z. Li, "A New AL-FEC Coding Scheme for Mobile Video Broadcasting with Limited Feedback", IEEE Mutimedia Signal Processing (MMSP) Workshop, Montreal, Canada, 2016.
    3. Z. Li, S. Zhao, D. Medhi, and I. Bouazizi, "Wireless Video Traffic Bottleneck Coordination with DASH SAND Framework", IEEE Visual Communication and Image Processing (VCIP) Conf, Chengdu, China, 2016.
    4. S. Zhao, Z. Li, and D. Medhi, "Low Delay MPEG DASH Streaming over the WebRTC Data Channel", IEEE PacketVideo Workshop , Seattle, 2016.
    5. S. Xie, Y.-L, Xu, and Z. Li, "DASH Sub-Representation with Temporal QoE Driven Layering", IEEE PacketVideo Workshop , Seattle, 2016.
    6. S. Zhao, Z. Li, and D. Medhi, "Low Delay Streaming of DASH Content with WebRTC Data Channel", IEEE/ACM Int'l Workshop on Quality of Service (IWQoS), Beijing, 2016.
    7. D. Noor, Z. Li, and A. Nagar, " ROBUST OBJECT RE-IDENTIFICATION WITH GRASSMANN SUBSPACE FEATURE FOR KEY POINTS AGGREGATION", IEEE Int'l Conf on Image Processing, Arizona, 2016.
    2010-2015
    1. Z. Zheng, Z. Li, A. Nagar, "Compact Deep Neural Networks for Device-Based Image Classification", book chapter, Mobile Cloud Visual Media Computing, Springer-Verlag, 2015: 201-217.
    2. Z. Zheng, Z. Li, A. Nagar, and W. Kang, "Compact Deep Neural Network for Device Based Image Classification", IEEE Int'l Conf on Multimedia & Expo (ICME). [PDF]
    3. V. Fragoso, G. Srivastava, A. Nagar, Z. Li, K. Park, and M. Turk, "Cascade of Box (CABOX) Filters for Optimal Scale Space Approximation", Proc of the 4th IEEE Int'l Workshop on Mobile Vision , Columbus, USA, 2014. [PDF]
    4. A. Nagar, Z. Li, G. Srivastava, and K. Park, "AKULA: Adaptive Cluster Aggregation for Visual Search", IEEE Data Compression Conference (DCC), 2014. [PDF]
    5. Z. Li, and I. Bouazizi, "Light Weight Content Fingerprinting for Video Playback Verification in MPEG DASH", Proceedings of IEEE PacketVideo, San Jose, 2013. [PDF]
    6. X. Xin, A. Nagar, G. Srivastava, Z. Li, F. Fernandes, A. Katsaggelos,Large Visual Repository Search with Hash Collision Design Optimization. IEEE MultiMedia 20(2): 62-71 (2013).
    7. X. Xin, Zhu Li, A. K. Katsaggelos, "Laplacian embedding and key points topology verification for large scale mobile visual identification", Signal Processing: Image Communication vol. 28(4): 323-333 (2013).
    8. J. Yuan, G. Zhao, Y. Fu, Z. Li, A. K. Katsaggelos, Y. Wu," Discovering Thematic Objects in Image Collections and Videos", IEEE Trans. on Image Processing vol.21(4): 2207-2219 (2012).
    9. W. Ji, Z. Li, and Y. Chen, "Joint Source-Channel Coding Optimization for Layered Video Broadcasting to Heterogeneous Devices", IEEE Trans. on Multimedia, vol.14(2): 443-455 (2012).
    10. H. Xu, J. Wang, Z. Li, G. Zeng, S. Li,"Complementary Hashing for Approximate Nearest Neighbor Search", IEEE Int'l Conference on Computer Vision (ICCV), Barcelona, Spain, 2011. [PDF]
    11. X. Wang, Z. Li, and D. Tao, "Subspace Indexing on Grassmann Manifold for Large Scale Multimedia Retrieval", IEEE Trans. on Image Processing, vol.20(9): 2627-2635 (2011). [PDF]
    12. B. Liu, Z. Li, L. Lin, and M. Wang, "Real-Time Video Copy Location Detection in Large Scale Repository ", IEEE Multimedia vol. 18(3): 22-31 (2011). [PDF]
    13. X. Wang, Z. Li, L. Zhang, and J. Yuan, "Grassmann Hashing for Approx Nearest Neighbour Search in High Dimensional Space", Proc. of IEEE Int'l Conf on Multimedia & Expo (ICME), Barcelona, Spain, 2011. [PDF]
    Recent News
    2016-18, 2020, 2022 AFRL visiting faculty at the USAF Academy, falling in love with Colorado 14ers: Mt. Antero (14269') , Mt. Elbert (14433'), Mt. Harvard (14420') , Mt. Massive (14421'), Mt. Lincoln (14286') , Grays Peak (14279'), Quandary(14265'), Princeton (14197'), Belford (14197') , La Plata (14334'), Huron Peak(14006'), Redcloud (14037') & Sunshine (14001'), Shavano (14230'), and Pikes Peak (14109').

    News

    2 ECE faculty positions at UMKC, in area of RF/Electromagnetics and Robotics/Control.

    2022.10, Tutorial "Sparse Conv in Point Cloud Upscaling, Motion Compensation and Deblocking" at ICIP 2022, Bordeaux, talk video and slides are available.

    2022.03, invited talk at Facebook on "Deep Learning in Immersive Media Compression", slides

    2022.03, A new award from NSF on Immersive Media Communication over 5G/6G Networks, joint with Prof. Shiwen Mao at Auburn Univ. Thanks to NSF ! Recruiting new PhD student.

    2022.02, Deep Learning in Point Cloud Compression and Processing, invited talk at CityU.

    2021.10, IEEE Trans on Circuits & System for Video Tech is recruiting new AEs for 2022.01-2023.12 term, please refer to T-CSVT AE Opening for more details.

    2021.07, NSF-AFRL supplement grant ($110K) to support research in sensor fusion and remote sensing research with Dr. Asif Mehmood at AFRL/RYAT.

    2020.08, NEH (National Endowment for Humanity) Grant for HSI imaging in ancient scripture analysis (PI: Jeff Rydberg-Cox, Dept of English).    

    Announcements

    PhD Scholarships are available for 2 self-motivated students. Ideal candidates should have an MS degree in CS/EE and have solid programming in C, Python, and MATLAB. Visiting scholars are welcome. If interested, send me a brief email at: lizhu@umkc.edu.
    For more details, click here.