题 目：Scale-adaptive Low-resolution Person Re-identification
讲 者：Dr. Zheng Wang
时 间：2018年11月 20日15:50-17:25
地 点： 国家多媒体软件工程技术中心6楼南613会议室
Person re-identification is an important task in video surveillance and forensics applications. Most of previous approaches are based on a key assumption that all person images have uniform and sufficiently high resolutions. Actually, various low-resolutions and scale mismatching always exist in open world. We name this kind of problem as Scale-Adaptive Low-Resolution Person Re-identification (SALR-REID). We proposed two methods for this task, i.e., (1) learning discriminating surface for scale-distance function (SDF) and (2) Cascaded Super-Resolution GAN (CSR-GAN). Extensive evaluations on two simulated datasets and one public dataset demonstrate the advantages of these two methods.
Zheng Wang received the Ph.D. degree at Wuhan University in 2017. He is a JSPS Postdoctoral Fellowship Researcher (日本学術振興会特別研究員) at National Institute of Informatics (NII), Japan. He was working under the JST CREST project "Experience and Action Sensing of Media Consumers based on Unknown Target Retrieval and Recognition Framework". He has published over 10 research papers in top-tier journals and conferences, including IEEE Transactions on Image Processing (TIP), IEEE Transactions on Cybernetics (TCYB), IEEE Transactions on Multimedia (TMM), IJCAI, ACM Multimedia. He has won the best paper award of PCM 2014, and ACM Wuhan Doctoral Dissertation Award. His current research interests include instance search and multimedia data mining.