Technical Program

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TA.P7: Visual Saliency

Session Type: Poster
Time: Tuesday, October 9, 10:30 - 12:10
Location: Poster Area 7
Session Chair: Tiago Carvalho, Federal Institute of São Paulo
 
 TA.P7.1: WEIGHTED LINEAR DISCRIMINANT ANALYSIS BASED ON CLASS SALIENCY INFORMATION
         Lei Xu; Tampere University of Technology
         Alexandros Iosifidis; Aarhus University
         Moncef Gabbouj; Tampere University of Technology
 
 TA.P7.2: ANISOTROPIC PARTIAL DIFFERENTIAL EQUATION BASED VIDEO SALIENCY DETECTION
         Wai Lam Hoo; University of Malaya
         Chee Seng Chan; University of Malaya
 
 TA.P7.3: VISUAL SALIENCY ANALYSIS FOR COMMON REGION OF INTEREST DETECTION IN MULTIPLE REMOTE SENSING IMAGES
         Libao Zhang; Beijing Normal University
         Qiaoyue Sun; Beijing Normal University
         Yang Sun; Beijing Normal University
 
 TA.P7.4: GRAPH-BASED SALIENCY FUSION WITH SUPERPIXEL-LEVEL BELIEF PROPAGATION FOR 3D FIXATION PREDICTION
         Bei Li; Huazhong University of Science and Technology
         Qiong Liu; Huazhong University of Science and Technology
         Xiang Shi; Huazhong University of Science and Technology
         You Yang; Huazhong University of Science and Technology
 
 TA.P7.5: BILLBOARD SALIENCY DETECTION IN STREET VIDEOS FOR ADULTS AND ELDERLY
         Onkar Krishna; The University of Tokyo
         Kiyoharu Aizawa; The University of Tokyo
 
 TA.P7.6: DO DEEP-LEARNING SALIENCY MODELS REALLY MODEL SALIENCY?
         Phutphalla Kong; Institute of Technology of Cambodia
         Matei Mancas; University of Mons
         Nimol Thuon; Institute of Technology of Cambodia
         Seng Kheang; Institute of Technology of Cambodia
         Bernard Gosselin; University of Mons
 
 TA.P7.7: SALIENT TARGET DETECTION BASED ON THE COMBINATION OF SUPER-PIXEL AND STATISTICAL SALIENCY FEATURE ANALYSIS FOR REMOTE SENSING IMAGES
         Libao Zhang; Beijing Normal University
         Yue Wang; Beijing Normal University
         Yang Sun; Beijing Normal University
 
 TA.P7.8: ROBUST SALIENT OBJECT DETECTION VIA FUSING FOREGROUND AND BACKGROUND PRIORS
         Kan Huang; Peking University
         Chunbiao Zhu; Peking University
         Ge Li; Peking University