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供稿:    責任編輯:安果    時間:2018-05-18    閱讀:





報告題目:Delving into Deep Features for Saliency Detection




Saliency detection has achieved great success in computer vision applications. However, accurate saliency detection remains an unsolved problem because there are large variety of facts that cancontribute to define visual saliency, and it’s hard to combineall cues in an appropriate way. In this report, I will introduce our recent works on saliency detection, especially in different fully convolutional network models, which based on the hierarchical facts in deep neural networks. Our methods include:1) aggregating multi-level convolutionalfeature for salient object detection in complex scenes.2)learning deep uncertain convolutionalfeatures for boosting saliency detection, which encourage the confident boundaries of objects. 3) a stage-wise refinement model, in which a pyramid pooling moduleis applied for global context aggregation.4)based on the intrinsic reflectionof images, we decompose the input images into lossless reflection pairs to learn complementary features for saliency detection.Experimental evaluations on public benchmarksshow that our proposed methods compares favorably againstthe state-of-the-art approaches.


張平平博士現為澳大利亞視覺技術研究中心(ACVT)研究員. 他分別于2012年、2018年在河南師范大學、大連理工大學獲得理學學士、工學博士學位。師從大連理工大學盧湖川教授,其主要研究興趣為計算機視覺與機器學習。他已在國際計算機視覺和人工智能頂級會議(如ICCV,ECCV,IJCAI)以及期刊(如TIP,TCSVT,PR)上發表論文十數篇,并擔任多個會議及期刊的審稿人,如CVPR,ICCV,ECCV,IJCAI,TPAMI,IJCV,TIP等。

Dr. Pingping Zhangis a research in Australian Centre of Visual Technology. In 2012 and 2018, He received the B.S. and Ph.D degree from Henan Normal University (HNU) and Dalian University of Technology (DUT), respectively. His supervisor is Prof. Huchuan Lu. His main research interests are in computer vision and machine learning. He has published more than 10 papers in top conferences/journals of computer vision and artificial intelligence, including ICCV, ECCV,IJCAI,TIP TCSVT,PR,etc. He also serves as the reviewer CVPR,ICCV,ECCV,IJCAI,TPAMI,IJCV,TIP,etc..