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@inproceedings{bb156861,
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        BOOKTITLE = ECCV18,
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@inproceedings{bb156862,
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        BOOKTITLE = ECCV18,
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@inproceedings{bb156863,
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        TITLE = "GeoDesc: Learning Local Descriptors by Integrating Geometry Constraints",
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        YEAR = "2018",
        PAGES = "IX: 170-185",
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@inproceedings{bb156864,
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Networks",
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        YEAR = "2018",
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@inproceedings{bb156865,
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        BOOKTITLE = ICIP17,
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@inproceedings{bb156866,
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        BOOKTITLE = ICIP17,
        YEAR = "2017",
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@inproceedings{bb156867,
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        TITLE = "Discriminative canonical correlation analysis network for image
classification",
        BOOKTITLE = ICIP17,
        YEAR = "2017",
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@inproceedings{bb156868,
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        TITLE = "4D effect classification by encoding CNN features",
        BOOKTITLE = ICIP17,
        YEAR = "2017",
        PAGES = "1812-1816",
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@inproceedings{bb156869,
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        YEAR = "2017",
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@inproceedings{bb156870,
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        TITLE = "Improved Descriptors for Patch Matching and Reconstruction",
        BOOKTITLE = CEFR-LCV17,
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@inproceedings{bb156871,
        AUTHOR = "Zoumpourlis, G. and Doumanoglou, A. and Vretos, N. and Daras, P.",
        TITLE = "Non-linear Convolution Filters for CNN-Based Learning",
        BOOKTITLE = ICCV17,
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@inproceedings{bb156872,
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        TITLE = "Fast Image Processing with Fully-Convolutional Networks",
        BOOKTITLE = ICCV17,
        YEAR = "2017",
        PAGES = "2516-2525",
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@inproceedings{bb156873,
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        TITLE = "RON: Reverse Connection with Objectness Prior Networks for Object
Detection",
        BOOKTITLE = CVPR17,
        YEAR = "2017",
        PAGES = "5244-5252",
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@inproceedings{bb156874,
        AUTHOR = "Worrall, D.E. and Brostow, G.J.",
        TITLE = "CubeNet: Equivariance to 3D Rotation and Translation",
        BOOKTITLE = ECCV18,
        YEAR = "2018",
        PAGES = "VI: 585-602",
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@inproceedings{bb156875,
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        BOOKTITLE = CVPR17,
        YEAR = "2017",
        PAGES = "4961-4970",
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@inproceedings{bb156876,
        AUTHOR = "Ren, J. and Chen, X.H. and Liu, J.B. and Sun, W.X. and Pang, J.H. and Yan, Q. and Tai, Y.W. and Xu, L.",
        TITLE = "Accurate Single Stage Detector Using Recurrent Rolling Convolution",
        BOOKTITLE = CVPR17,
        YEAR = "2017",
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@inproceedings{bb156877,
        AUTHOR = "Stone, A. and Wang, H. and Stark, M. and Liu, Y. and Phoenix, D.S. and George, D.",
        TITLE = "Teaching Compositionality to CNNs",
        BOOKTITLE = CVPR17,
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@inproceedings{bb156878,
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        TITLE = "Exploring the Granularity of Sparsity in Convolutional Neural
Networks",
        BOOKTITLE = Tensor17,
        YEAR = "2017",
        PAGES = "1927-1934",
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@inproceedings{bb156879,
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        TITLE = "Euclidean output layer for discriminative feature extraction",
        BOOKTITLE = ICIVC17,
        YEAR = "2017",
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@inproceedings{bb156880,
        AUTHOR = "Zhao, J.P. and Chang, C.K. and Itti, L.",
        TITLE = "Learning to Recognize Objects by Retaining Other Factors of Variation",
        BOOKTITLE = WACV17,
        YEAR = "2017",
        PAGES = "560-568",
        BIBSOURCE = "http://www.visionbib.com/bibliography/pattern651.html#TT152750"}

@inproceedings{bb156881,
        AUTHOR = "Ke, T.W. and Lin, C.W. and Liu, T.L. and Geiger, D.",
        TITLE = "Variational Convolutional Networks for Human-Centric Annotations",
        BOOKTITLE = ACCV16,
        YEAR = "2016",
        PAGES = "IV: 120-135",
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@inproceedings{bb156882,
        AUTHOR = "Song, Y. and Wang, P.S. and Hong, X.H. and McLoughlin, I.",
        TITLE = "Fisher vector based CNN architecture for image classification",
        BOOKTITLE = ICIP17,
        YEAR = "2017",
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@inproceedings{bb156883,
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        TITLE = "Image classification with CNN-based Fisher vector coding",
        BOOKTITLE = VCIP16,
        YEAR = "2016",
        PAGES = "1-4",
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@inproceedings{bb156884,
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        TITLE = "Self-Supervised Video Representation Learning with Odd-One-Out
Networks",
        BOOKTITLE = CVPR17,
        YEAR = "2017",
        PAGES = "5729-5738",
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@inproceedings{bb156885,
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        TITLE = "Joint Learning of Convolutional Neural Networks and Temporally
Constrained Metrics for Tracklet Association",
        BOOKTITLE = DeepLearn-C16,
        YEAR = "2016",
        PAGES = "386-393",
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@inproceedings{bb156886,
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        TITLE = "An Empirical Evaluation of Current Convolutional Architectures:
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        BOOKTITLE = CVPR16,
        YEAR = "2016",
        PAGES = "4442-4451",
        BIBSOURCE = "http://www.visionbib.com/bibliography/pattern651.html#TT152756"}

@inproceedings{bb156887,
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        TITLE = "Scene Recognition with CNNs: Objects, Scales and Dataset Bias",
        BOOKTITLE = CVPR16,
        YEAR = "2016",
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@inproceedings{bb156888,
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        BOOKTITLE = CVPR16,
        YEAR = "2016",
        PAGES = "280-288",
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@inproceedings{bb156889,
        AUTHOR = "Noh, H. and Seo, P.H. and Han, B.",
        TITLE = "Image Question Answering Using Convolutional Neural Network with
Dynamic Parameter Prediction",
        BOOKTITLE = CVPR16,
        YEAR = "2016",
        PAGES = "30-38",
        BIBSOURCE = "http://www.visionbib.com/bibliography/pattern651.html#TT152759"}

@inproceedings{bb156890,
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        BOOKTITLE = ECCV16,
        YEAR = "2016",
        PAGES = "VI: 434-450",
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@inproceedings{bb156891,
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        TITLE = "Top-Down Learning for Structured Labeling with Convolutional
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        BOOKTITLE = ECCV16,
        YEAR = "2016",
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@inproceedings{bb156892,
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Networks",
        BOOKTITLE = ECCV16,
        YEAR = "2016",
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@inproceedings{bb156893,
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        BOOKTITLE = ECCV16,
        YEAR = "2016",
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@inproceedings{bb156894,
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        BOOKTITLE = ECCV16,
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@inproceedings{bb156895,
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        TITLE = "Design of Kernels in Convolutional Neural Networks for Image
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        YEAR = "2016",
        PAGES = "VII: 51-66",
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@inproceedings{bb156896,
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        BOOKTITLE = ECCV16,
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@inproceedings{bb156897,
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        YEAR = "2016",
        PAGES = "III: 143-155",
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@inproceedings{bb156898,
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        TITLE = "Video system for human attribute analysis using compact convolutional
neural network",
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        YEAR = "2016",
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@inproceedings{bb156899,
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        TITLE = "Unsupervised convolutional neural networks for motion estimation",
        BOOKTITLE = ICIP16,
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