Dr. Wu Liu is a Senior Researcher in JD AI Research, China. His current research interests include human behavior analysis and intelligent video surveillance. He received his Ph.D. degree from the Institute of Computing Technology, Chinese Academy of Science in 2015. He has published more than 60 papers in prestigious conferences and journals in computer vision and multimedia. He received IEEE Trans. on Multimedia 2019 Prize Paper Award, IEEE Multimedia 2018 Best Paper Award, IEEE ICME 2016 Best Student Paper Award, and Chinese Academy of Sciences Outstanding Ph.D. Thesis Award in 2016, etc. He also won the 1st Place in the single and multi-person pose estimation tasks in CVPR 2018 Look into Person Challenge. Dr. Liu is the founding committee member of ACM FCA, and the committee member of IEEE CASS-MSA. He has also served as the Technical Program Chair of ACM MM Asia 2021, Web Chair of ICME 2019, Publicity Chair of BIGMM 2018, Industrial Chair of ChinaMM 2020~2021, and the Area Chairs of ACM MM 2019~2021, AAAI 2021, ISCAS 2021, ICME 2019, ICIP 2017, etc. Wu Liu also organized the workshops “Human-centric Multimedia Analysis” in ACM MM 2020 and 2021, the workshop “Human-centric Trustworthy Computer Vision From Research to Applications” in IEEE ICCV 2021, the grand challenge “106-Point Facial Landmark Localization” in IEEE ICME 2021, the workshop “Human and Vehicle Analysis for Intelligent Urban Computing” in IEEE ICPR 2020, the tutorials “Human Behavior Understanding":" From Human-Oriented Analysis to Action Recognition” in IEEE ICME 2019, the tutorials “Human-centric Visual Understanding” in ACM MM Asia 2019, the special issue on “Intelligent Urban Computing with Big Data” in MVA 2018, and the special issue on “Intelligent Analytics for Big Video Data” in MTAP 2019.

Dr. Xinchen Liu is a Senior Researcher as JD AI Research. His research interests include human-centric computer vision and its application in retail. He received the Ph.D. degree in computer science from Beijing University of Posts and Telecommunications in 2018. He received IEEE Trans. on Multimedia 2019 Prize Paper Award, IEEE ICME 2016 Best Student Paper Award, and Outstanding Doctoral Dissertation Award of China Society of Image and Graphics in 2019. Dr. Liu has won 1st Place in AI+Person Re-identification Track of National AI Challenge 2020, 2nd Place in Multi-Person Human Parsing Track of CVPR 2019 Look-into-Person Challenge, and 2nd in Single-Person Human Parsing Track of CVPR 2018 Look-into-Person Challenge. He also served as a PC member of ACM Multimedia, AAAI, ICME, etc.

Jingkuan Song is a full professor with University of Electronic Science and Technology of China (UESTC). His research interest includes large-scale multimedia retrieval, image/video segmentation and image/video understanding using hashing, graph learning and deep learning techniques. He joined Columbia University as a Postdoc Research Scientist (2016-2017), and University of Trento as a Research Fellow (2014-2016). He obtained his PhD degree in 2014 from The University of Queensland (UQ), Australia. He was the winner of the Best Paper Award in ICPR (2016, Mexico), Best Student Paper Award in Australian Database Conference (2017, Australia), and Best Paper Honorable Mention Award (2017, Japan). Jingkuan has served as the Demo Chair of ACM Multimedia Asia 2020, Workshop Chair of ApWeb 2019, and the Area Chairs of ACM MM 2018/2020, ICME 2020, etc. He severs as the Associate Editor for ACM Trans. on Multimedia Computing Communications and Applications. He is also the Guest Editor of IEEE TMM, ACM TDS, PR and he is PC member of CVPR’18-20, MM'18-20, IJCAI'18-20, etc.

Dingwen Zhang is a Professor at BRAIN Lab, NWPU. He obtained his B.S. and Ph.D. degrees from School of Automation, Northwestern Polytechnical University (NWPU) in 2012 and 2018, respectively. From Oct. 2015 to Oct. 2017, he worked with Dong Huang and Fernando de la Torre as a visiting PHD student at the Human Sensing Laboratory in Carnegie Mellon University. He is mainly interested in developing effective computer vision algorithms that are inspired by the human vison and human learning procedure. Currently, he is working on developing weakly supervised learning systems for computer vision tasks like object detection, segmentation, 3D shape reconstruction. He has published more than 30 peer-reviewed conference and journal papers, including CVPR, ICCV, IJCAI, AAAI, and IEEE T-PAMI, T-IP, T-NNLS, T-MM, IJCV. He served as a pc member of AAAI, NeurIPS, CVPR, ICCV, etc. Dingwen is the recipient of the CSIG Outstanding Doctoral Dissertation Award and ACM China SIGAI Outstanding Doctor Award in 2019. He is also the recipient of the Clarivate Highly Cited Researcher in 2019.

Wenbing Huang is now an assistant researcher at Tsinghua University, awarded as the Shuimu Tsinghua Scholar in 2019 and Tencent Rhino-Bird Visiting Scholar in 2020. Before this, he was a senior researcher at Tencent AI Lab during 2017 and 2019. He received the Ph.D. degree of computer science and technology from Tsinghua University in 2017 and the bachelor’s degree of mathematics from Beihang University in 2012. His current research mainly lies in the areas of machine learning computer vision, and robotics, with particular focus on learning on irregular structures including graphs and videos. He has published about 30 peer-reviewed top-tier conference and journal papers, including the Proceedings of NeurIPS, ICLR, ICML, CVPR, etc. He has won the Champion of Autonomous Grasp Challenges in IROS 2016. He served as a session chair of “Video":" Events, Activities and Surveillance” in IJCAI 2019, the pc member of IJCAI 2019-2020, AAAI 2019-2020, and the reviewer of TPAMI, IJCV, TIP, Neurocomputing, NeurIPS 2019, CVPR 2019-2020, ICML 2019-2020, ICCV 2019, ECCV 2020, AISTATS 2019-2020, ACMMM 2019. He was selected in the list of Top Reviewers in NeurIPS 2019.

Junbo Guo, Ph.D., is currently a researcher of the State Key Laboratory of Communication Content Cognition, People’s Daily Online. He has long been engaged in the research of technologies related to communication content cognition and Internet content security. He directed a range of research projects supported by National K&D Program of China. As one of major achievements of these research, the video content supervision systems have been applied in a number of national ministries and commissions. He received the first prize of Beijing Science and Technology Award three times.

Dr. John R. Smith is IEEE Fellow, IBM Fellow and manager of AI Tech for IBM Research AI at IBM T. J. Watson Research Center. He currently leads research and development on vision, speech, language, knowledge, and interaction in Yorktown Heights, NY USA. Previously he led IBM’s R&D on Computer Vision and Multimedia. Recent work includes":" Visual Recognition for IBM Watson Developer Cloud; Medical Image Analysis for Skin Cancer; Augmenting Creativity for Movie Trailers; Visual Comprehension of Dynamic Scenes in Video; Multi-modal Analysis for Sports Highlights Detection; Earlier, Dr. Smith was Distinguished Research Staff Member and Senior Manager of Intelligent Information Systems. He led the development of IBM Multimedia Analysis and Retrieval System (IMARS). Dr. Smith was a founding participant and served on the Advisory Committee for the NIST TRECVID Video Retrieval Evaluation. He led IBM's participation in TRECVID evaluations for more than a decade. Dr. Smith was co-General Chair of ACM Intl. Conf. on Multimedia Retrieval (ICMR-2016) in New York City. Previously, he was Editor-in-Chief of IEEE Multimedia from 2010 – 2014, Associate Editor-in-Chief from 2006 – 2010 and Standards Editor from 2003 – 2006. Earlier Dr. Smith led IBM's participation in MPEG-7 / MPEG-21 standards and was Chair of the MPEG Multimedia Description Schemes Sub-Group and co-project Editor of MPEG-7 Standard.