Computer vision expert Qi Tian joins Huawei Noah's Ark Laboratory as a chief scientist of computer vision

Jun. 2018


Recently, the computer vision expert Dr. Qi Tian, joined Huawei Noah’s Ark Laboratory as the chief scientist of computer vision. Dr. Tian was a Full Professor in the Department of Computer Science, the University of Texas at San Antonio (UTSA) before he took the position in Huawei Noah’s Ark Lab. He is an IEEE fellow, a Changjiang Chaired Professor of the Ministry of Education, and was elected as one of the 2016 Most Influential Scholars in Multimedia by He will lead the fundamental research on computer vision, and land the research to various applications such as Safe City, Terminal Vision, Autonomous Driving and GTS Brain in the lab.

Dr. Tian received his Ph.D. (advisor Thomas S. Huang, Member of NAE, Foreign Member of Chinese Academy of Sciences, Foreign Member of Chinese Academy of Engineering) in ECE from University of Illinois at Urbana-Champaign (UIUC) in 2002 and received his B.E. in Electronic Engineering from Tsinghua University in 1992 and M.S. in ECE from Drexel University in 1996, respectively. Dr. Tian’s research interests include computer vision, multimedia content analysis, image and video indexing and retrieval, and machine learning, and published over 440 refereed journal and conference papers (including 110+ IEEE/ACM Transactions and 90 CCF A Category Conference Papers). His Google citiations are over 11,600 with h-index of 58. He was the co-author of a Best Paper in ACM ICMR 2015, a Best Paper in PCM 2013, a Best Paper in MMM 2013, a Best Paper in ACM ICIMCS 2012, a Top 10% Paper Award in MMSP 2011, a Best Student Paper in ICASSP 2006, and co-author of a Best Student Paper Candidate in ICME 2015, and a Best Paper Candidate in PCM 2007.

Dr. Tian has served as founding member of International Steering Committee for ACM International Conference on Multimedia Retrieval (ICMR, 2009-2014), ACM Multimedia Conference Review Committee Member (2009-), and International Steering Committee Member for ACM MIR (2006-2010), the chair of selection committee for 2018 SIGMM outstanding Thesis in Multimedia Computing Communications and Applications, Best Paper Committee Selection Co-Chair for IEEE ICME 2016, Best Paper Committee Co-Chair for IEEE Transactions on Multimedia 2014 and 2015, ACM Multimedia 2015; Best Paper Commitee Member for ACM Multimedia 2009, ACM ICIMCS 2013, ICME 2006 and 2009, PCM 2012, and IEEE International Symposium on Multimedia 2011. He has served as General Chair for ACM Multimedia 2015, MMM 20156; Program Coordinator for ACM Multimedia 2009, and Technical Program Chairs for various international conferences including ACM ICMR 2018, ACM CIVR 2010, ACM ICMCS 2009, MMM 2010, IMAI 2007, VIP 2007, 2008, MIR 2005. He has also served in various organization committees as Panel and Tutorial Chair, Publicity Chair, Special Session Chair, Track Chair in numerous ACM and IEEE conferences such as ACM Multimedia, VCIP, PCM, CIVR, ICME, and served as TPC members for prestigious conferences such as ACM Multimedia, SIGIR, ICCV, CVPR, and KDD.

Dr. Tian’s research projects were funded by ARO, NSF, DHS, Google, FXPAL, NEC, Blippar, SALSI, CIAS, Akiira Media Systems, HP and UTSA. He received 2017 UTSA President Distinguished Award for Research Achievement, 2016 UTSA Innovation Award in the first category, 2014 Research Achievement Awards from College of Science, UTSA, and 2010 Google Faculty Research Award. He received 2010 ACM Service Award. He is the Associate Editor of IEEE Transactions on Multimedia (TMM), IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), ACM Transactions on Multimedia Computing, Communications and Applications (TOMM), Multimedia System Journal (MMSJ), and in the Editorial Board of Journal of Multimedia (JMM) and Journal of Machine Vision and Applications (MVA). Dr. Tian is the Leading Guest Editor of IEEE Transactions on Multimedia, Journal of Computer Vision and Image Understanding, etc. Dr. Tian is a Fellow of IEEE and a Member of ACM.

Computer vision is one of the major research directions in Huawei Noah’s Ark Lab. It focuses on using machine learning methods to enable the machine to recognize and understand the surrounding world, and its research field includes fundamental image quality enhancement, semantic image understanding and inference, 3D reconstruction, and et al. In combination with the company's business, our research in computer vision covers multiple application directions such as terminal vision, safe city, autonomous driving, and GTS brain. In terminal vision, we focus on using AI algorithm to design for new HUAWEI terminals visual experience, including intelligent scene recognition, saliency detection, image semantic segmentation, image color balance, image super resolution and denoising, OCR, image search, image captioning and so on. For safe city, based on crowd-aware monitoring video content analysis tasks, we focus on challenging issues such as “unclear”, “not sure”, “unable to found”, and “number wrong” in video surveillance, by breaking through the key technologies of image quality enhancement, human attribute recognition, monitoring face recognition, multimode biometric fusion, video event analysis, etc. The solutions will be verified in real-world business scenarios and iterated to promote technology commercially. In autonomous driving, we combine different kinds of sensors to recognize and understand the objects and environment both inside and outside of the vehicles. In GTS brain, we focus on using artificial intelligence algorithms and systems to promote intelligent and smart transformation of network O&M, and lay a solid foundation for future O&M services of tens of billions of dollars in inventory networks. This includes an industrial AR assistant system constructed based on machine vision such as object detection and tracking, SLAM to improve network operation efficiency. After Prof. Tian join the lab, he will make full use of his experience and impact in the society to strengthen the research on fundamental problems of computer vision, and enhance the algorithm development abilities on applications such as safe city, terminal vision, autonomous driving and GTS brain.