视觉注意力检测综述
作者:
作者简介:

王文冠(1990-),男,河北磁县人,博士,CCF学生会员,主要研究领域为计算机视觉,人工智能;沈建冰(1978-),男,博士,教授,博士生导师,CCF专业会员,主要研究领域为计算机视觉,人工智能;贾云得(1962-),男,博士,教授,博士生导师,CCF杰出会员,主要研究领域为计算机视觉,人工智能.

通讯作者:

沈建冰,E-mail:shenjianbing@bit.edu.cn

基金项目:

国家自然科学基金(61673062);北京市自然科学基金(4182056)


Review of Visual Attention Detection
Author:
Fund Project:

National Natural Science Foundation of China (61673062); Natural Science Foundation of Beijing Municipality (4182056)

  • 摘要
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  • 访问统计
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  • 参考文献 [27]
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  • 相似文献 [20]
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  • 引证文献
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  • 文章评论
    摘要:

    人类能够迅速地选取视野中的关键部分,选择性地将视觉处理资源分配给这些视觉显著的区域.在计算机视觉领域,理解和模拟人类视觉系统的这种注意力机制,得到了学界的大力关注,并显示出了广阔的应用前景.近年来,随着计算能力的增强以及大规模显著性检测数据集的建立,深度学习技术逐渐成为视觉注意力机制计算和建模的主要手段.综述了视觉注意力检测的最新研究进展,包括人眼关注点检测和显著物体检测,并讨论了当前流行的视觉显著性检测数据集和常用的评估指标.对基于深度学习的工作进行了综述,也对之前代表性的非深度学习模型进行了讨论,同时,对这些模型在不同的数据集上的性能进行了详细评估.最后探讨了该领域的研究趋势和未来的发展方向.

    Abstract:

    Humans have ability to quickly select a subset of the visual input and allocate processing resources to those visually important regions. In computer vision community, understanding and emulating such attention mechanism of the human visual system has attracted much attention from the researchers and shown a wide range of applications. More recently, with the ever increasing computational power and availability of large-scale saliency datasets, deep learning has become a popular tool for modeling visual attention. This review includes the recent advances in visual attention modeling, including fixation prediction and salient object detection. It also discusses popular visual attention benchmarks and various evaluation metrics. The emphasis of this review is both on the deep learning based studies and the represented non-deep learning models. Extensive experiments are also performed on various benchmarks for evaluating the performance of those visual attention models. In the end, the review highlights current research trends and provides insight into the future direction.

    参考文献
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̄潛渱??潝洠灚畨瑡敮牧?噐楐猬椠潗湡?慧渠摄?倠慌瑵琠效牃測?剗敡据潧朠湈楙琬椠潙湩??自ぃ???????????????扲牴?孩?ㄠ嵣?剮潶摯牬極杴畩敯穮??????桴浵敲摥????卲栠慡档?????捥琠楳潡湬?浥慮捣桹?慤?獴灥慣瑴楩潯?琮攠浉灮漺牐慲汯?洮愠硯楦洠畴浨?愠癉故牅慅朠敉?捴漧牬爠敃汯慮瑦椮漠湯?栠敃楯杭桰瑵?晥楲氠瑖敩牳?景潮爮?愲挰琱椷漮渠′爱攲挭漲朲渱椮琼楢潲渾???渴?倠牗潡据??潔晔?琠桂敯???????潚湨晡??漠湌??漠浚灨畡瑮敧爠?噐椬猠楌潵渠?慃渮搠?倠慳瑴瑡敧牥湷?剳敥挠潲来湦楩瑮楥潭湥??㈠ねは???ㄠ????扤牥?孥??嵩??琠瑳楡?????甠瑯潢浪慥瑣楴捳?晩潮瘠敩慭瑡楧潥湳?映潉牮?癐楲摯散漮?捯潦洠灴牨敥猠獉楅潅湅?畉獮楴渧杬?慃?湮敦甮爠潯扮椠潃汯潭杰極捴慥汲?浖潩摳敩汯?漮映′瘰椱猷甮愠水‰愳琹琭攴渰琴椸漮渼??????‵呝爠慃湨獥??潘湗??浚慨来敮?倠牁潌挬攠獌獩椠湊本????う???????????っ????ㄠ???戠牳?孧??嵮??慆摩楮穤慩摮敧栠?????湡牬楩煥畮整稠??????慳樠楩据??噭???祳攠?瑩牡愠捴歷楯渭杳?摲慥瑡慭戠慦獩數?晴潩牯?慳?獭敡瑮?潩晣?獃瑎慎湳搮愠牉摮?癐楲摯散漮?獯敦焠畴敨湥挠敉獅???????呬爠慃湯獮??漠湯??浃慯杭数?側牥潲挠敖獩獳楩湯杮??有??祝?㈠??特???????????扛爱?嬶??嵗?呮獧愠楔?????污慮杧朠????剌敵栠杈??????漠瑃椬漠湑?挠潊桑攮爠敋湥瑲?瑥牬慩捺步楤渠杳?睢楳瑰桡?浥甠汲瑡楮?汩慮执攠汦??删??潬灩瑥楮浣楹稠慤瑥楴潥湣???湮?倠牉潮挺??潯晣?琠桯敦??牨楥琠楅獵桲??慥捡桮椠湃敯?噦椮猠楯潮渠??潭湰晵?????ど?????ㄠ??戱父?嬠??崰??椶??堼???楛洱?吷???畯浮慧礠畈湍????呮獧愠楗????剨敥桮朠?????器楡摯攠潓?猬攠杌浡敭渠瑋慍琮椠潐湹?扡祭?瑤爠慤捩歬楡湴来?洠慤湥祥?晥楲朠畣牯敮?杌牓潔畍渠摦?獲攠杶浩敤湥瑯猠???湩?偮牴漠捯??潥晣? detection. In:Proc. of the European Conf. on Computer Vision. 2018. 715-731.
    [118] Leventhal AG. Vision and Visual Dysfunction:The Neural Basis of Visual Function. 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王文冠,沈建冰,贾云得.视觉注意力检测综述.软件学报,2019,30(2):416-439

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