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My ICASSP 2020 Schedule

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WE3.I: Machine Learning For Image/Video Processing III

Session Type: Lecture
Time: Wednesday, 6 May, 16:30 - 18:30
Location: On-Demand
Session Chair: Amit Roy-Chowdhury, University of California, Riverside
 
   WE3.I.1: SOLVING MISSING-ANNOTATION OBJECT DETECTION WITH BACKGROUND RECALIBRATION LOSS
         Han Zhang; Carnegie Mellon University
         Fangyi Chen; Carnegie Mellon University
         Zhiqiang Shen; Carnegie Mellon University
         Qiqi Hao; Beihang University
         Chenchen Zhu; Carnegie Mellon University
         Marios Savvides; Carnegie Mellon University
 
   WE3.I.2: FACE FEATURE RECOVERY VIA TEMPORAL FUSION FOR PERSON SEARCH
         Cheng-Yu Fan; National Taiwan University
         Chao-Peng Liu; National Taiwan University
         Kuan-Chun Wang; National Taiwan University
         Jiun-Hao Jhan; National Taiwan University
         Yu-Chiang Frank Wang; National Taiwan University
         Jun-Cheng Chen; Academia Sinica
 
   WE3.I.3: EDGEFOOL: AN ADVERSARIAL IMAGE ENHANCEMENT FILTER
         Ali Shahin Shamsabadi; Queen Mary University of London
         Changjae Oh; Queen Mary University of London
         Andrea Cavallaro; Queen Mary University of London
 
   WE3.I.4: FACIAL FEATURE EMBEDDED CYCLEGAN FOR VIS-NIR TRANSLATION
         Huijiao Wang; Wuhan University
         Haijian Zhang; Wuhan University
         Lei Yu; Wuhan University
         Li Wang; Agency for Science, Technology and Research (A*STAR)
         Xulei Yang; Agency for Science, Technology and Research (A*STAR)
 
   WE3.I.5: DEEP IMAGE DEBLURRING USING LOCAL CORRELATION BLOCK
         Wei Su; Northwestern Polytechnical University
         Yuan Yuan; Northwestern Polytechnical University
         Qi Wang; Northwestern Polytechnical University
 
   WE3.I.6: GLOBAL STRUCTURE GRAPH GUIDED FINE-GRAINED VEHICLE RECOGNITION
         Chuanming Wang; Beijing University of Posts and Telecommunications
         Huiyuan Fu; Beijing University of Posts and Telecommunications
         Huadong Ma; Beijing University of Posts and Telecommunications