{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:35:27Z","timestamp":1750221327010,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":44,"publisher":"ACM","license":[{"start":{"date-parts":[[2017,10,23]],"date-time":"2017-10-23T00:00:00Z","timestamp":1508716800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2017,10,23]]},"DOI":"10.1145\/3123266.3123417","type":"proceedings-article","created":{"date-parts":[[2017,10,20]],"date-time":"2017-10-20T13:04:26Z","timestamp":1508504666000},"page":"1600-1608","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":48,"title":["Selective Deep Convolutional Features for Image Retrieval"],"prefix":"10.1145","author":[{"given":"Tuan","family":"Hoang","sequence":"first","affiliation":[{"name":"Singapore University of Technology and Design, Singapore, Singapore"}]},{"given":"Thanh-Toan","family":"Do","sequence":"additional","affiliation":[{"name":"University of Adelaide, Adelaide, Australia"}]},{"given":"Dang-Khoa","family":"Le Tan","sequence":"additional","affiliation":[{"name":"Singapore University of Technology and Design, Singapore, Singapore"}]},{"given":"Ngai-Man","family":"Cheung","sequence":"additional","affiliation":[{"name":"Singapore University of Technology and Design, Singapore, Singapore"}]}],"member":"320","published-online":{"date-parts":[[2017,10,23]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"crossref","unstructured":"Relja Arandjelovi\u0107 Petr Gronat Akihiko Torii Tomas Pajdla and Josef Sivic. 2016. NetVLAD: CNN architecture for weakly supervised place recognition CVPR.  Relja Arandjelovi\u0107 Petr Gronat Akihiko Torii Tomas Pajdla and Josef Sivic. 2016. NetVLAD: CNN architecture for weakly supervised place recognition CVPR.","DOI":"10.1109\/CVPR.2016.572"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"crossref","unstructured":"Relja Arandjelovi\u0107 and Andrew Zisserman. 2012. Three things everyone should know to improve object retrieval CVPR.   Relja Arandjelovi\u0107 and Andrew Zisserman. 2012. Three things everyone should know to improve object retrieval CVPR.","DOI":"10.1109\/CVPR.2012.6248018"},{"volume-title":"Josephine Sullivan, Atsuto Maki, and Stefan Carlsson.","year":"2015","author":"Azizpour Hossein","key":"e_1_3_2_1_3_1"},{"key":"e_1_3_2_1_4_1","unstructured":"Artem Babenko and Victor Lempitsky. 2015. Aggregating Local Deep Features for Image Retrieval ICCV.  Artem Babenko and Victor Lempitsky. 2015. Aggregating Local Deep Features for Image Retrieval ICCV."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"crossref","unstructured":"Artem Babenko Anton Slesarev Alexandr Chigorin and Victor Lempitsky. 2014. Neural codes for image retrieval. In ECCV.  Artem Babenko Anton Slesarev Alexandr Chigorin and Victor Lempitsky. 2014. Neural codes for image retrieval. In ECCV.","DOI":"10.1007\/978-3-319-10590-1_38"},{"key":"e_1_3_2_1_6_1","unstructured":"Y-Lan Boureau Jean Ponce and Yann Lecun. 2010. A Theoretical Analysis of Feature Pooling in Visual Recognition ICML.   Y-Lan Boureau Jean Ponce and Yann Lecun. 2010. A Theoretical Analysis of Feature Pooling in Visual Recognition ICML."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/2964284.2967262"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/2502081.2502171"},{"volume-title":"Embedding based on function approximation for large scale image search. TPAMI","year":"2017","author":"Do Thanh-Toan","key":"e_1_3_2_1_9_1"},{"key":"e_1_3_2_1_10_1","unstructured":"Thanh-Toan Do Anh-Dzung Doan and Ngai-Man Cheung. 2016. Learning to hash with binary deep neural network. ECCV.  Thanh-Toan Do Anh-Dzung Doan and Ngai-Man Cheung. 2016. Learning to hash with binary deep neural network. ECCV."},{"volume-title":"Trung T Pham, and Ngai-Man Cheung.","year":"2017","author":"Do Thanh-Toan","key":"e_1_3_2_1_11_1"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"crossref","unstructured":"Thanh-Toan Do Quang Tran and Ngai-Man Cheung. 2015. FAemb: A function approximation-based embedding method for image retrieval CVPR.  Thanh-Toan Do Quang Tran and Ngai-Man Cheung. 2015. FAemb: A function approximation-based embedding method for image retrieval CVPR.","DOI":"10.1109\/CVPR.2015.7298978"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.81"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"crossref","unstructured":"Yunchao Gong Liwei Wang Ruiqi Guo and Svetlana Lazebnik. 2014. Multi-scale orderless pooling of deep convolutional activation features ECCV.  Yunchao Gong Liwei Wang Ruiqi Guo and Svetlana Lazebnik. 2014. Multi-scale orderless pooling of deep convolutional activation features ECCV.","DOI":"10.1007\/978-3-319-10584-0_26"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"crossref","unstructured":"Albert Gordo Jon Almazan Jerome Revaud and Diane Larlus. 2016. Deep Image Retrieval: Learning Global Representations for Image Search ECCV.  Albert Gordo Jon Almazan Jerome Revaud and Diane Larlus. 2016. Deep Image Retrieval: Learning Global Representations for Image Search ECCV.","DOI":"10.1007\/978-3-319-46466-4_15"},{"volume-title":"Deep Residual Learning for Image Recognition. arXiv preprint arXiv:1512.03385","year":"2015","author":"He Kaiming","key":"e_1_3_2_1_16_1"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"crossref","unstructured":"Herv\u00e9 J\u00e9gou and Ondvrej Chum. 2012. Negative Evidences and Co-occurences in Image Retrieval: The Benefit of PCA and Whitening ECCV.  Herv\u00e9 J\u00e9gou and Ondvrej Chum. 2012. Negative Evidences and Co-occurences in Image Retrieval: The Benefit of PCA and Whitening ECCV.","DOI":"10.1007\/978-3-642-33709-3_55"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"crossref","unstructured":"Herv\u00e9 J\u00e9gou Matthijs Douze and Cordelia Schmid. 2009. On the burstiness of visual elements. In CVPR.  Herv\u00e9 J\u00e9gou Matthijs Douze and Cordelia Schmid. 2009. On the burstiness of visual elements. In CVPR.","DOI":"10.1109\/CVPR.2009.5206609"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-009-0285-2"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"crossref","unstructured":"Herv\u00e9 J\u00e9gou Matthijs Douze Cordelia Schmid and Patrick P\u00e9rez. 2010. Aggregating local descriptors into a compact image representation CVPR.  Herv\u00e9 J\u00e9gou Matthijs Douze Cordelia Schmid and Patrick P\u00e9rez. 2010. Aggregating local descriptors into a compact image representation CVPR.","DOI":"10.1109\/CVPR.2010.5540039"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"crossref","unstructured":"Herv\u00e9 J\u00e9gou and Andrew Zisserman. 2014. Triangulation embedding and democratic aggregation for image search CVPR.  Herv\u00e9 J\u00e9gou and Andrew Zisserman. 2014. Triangulation embedding and democratic aggregation for image search CVPR.","DOI":"10.1109\/CVPR.2014.417"},{"volume-title":"Cross-dimensional Weighting for Aggregated Deep Convolutional Features ECCV Workshops.","year":"2016","author":"Kalantidis Yannis","key":"e_1_3_2_1_22_1"},{"key":"e_1_3_2_1_23_1","unstructured":"Alex Krizhevsky Ilya Sutskever and Geoffrey E Hinton. 2012. Imagenet classification with deep convolutional neural networks NIPS.   Alex Krizhevsky Ilya Sutskever and Geoffrey E Hinton. 2012. Imagenet classification with deep convolutional neural networks NIPS."},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/2964284.2967197"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"crossref","unstructured":"David G. Lowe. 1999. Object Recognition from Local Scale-Invariant Features ICCV.   David G. Lowe. 1999. Object Recognition from Local Scale-Invariant Features ICCV.","DOI":"10.1109\/ICCV.1999.790410"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/MMUL.2013.14"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"crossref","unstructured":"Florent Perronnin and Christopher Dance. 2007. Fisher Kernels on Visual Vocabularies for Image Categorization CVPR.  Florent Perronnin and Christopher Dance. 2007. Fisher Kernels on Visual Vocabularies for Image Categorization CVPR.","DOI":"10.1109\/CVPR.2007.383266"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"crossref","unstructured":"Florent Perronnin Jorge S\u00e1nchez and Thomas Mensink. 2010. Improving the fisher kernel for large-scale image classification ECCV.   Florent Perronnin Jorge S\u00e1nchez and Thomas Mensink. 2010. Improving the fisher kernel for large-scale image classification ECCV.","DOI":"10.1007\/978-3-642-15561-1_11"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"crossref","unstructured":"James Philbin Ondrej Chum Michael Isard Josef Sivic and Andrew Zisserman. 2007. Object retrieval with large vocabularies and fast spatial matching CVPR.  James Philbin Ondrej Chum Michael Isard Josef Sivic and Andrew Zisserman. 2007. Object retrieval with large vocabularies and fast spatial matching CVPR.","DOI":"10.1109\/CVPR.2007.383172"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"crossref","unstructured":"James Philbin Ondrej Chum Michael Isard Josef Sivic and Andrew Zisserman. 2008. Lost in quantization: Improving particular object retrieval in large scale image databases CVPR.  James Philbin Ondrej Chum Michael Isard Josef Sivic and Andrew Zisserman. 2008. Lost in quantization: Improving particular object retrieval in large scale image databases CVPR.","DOI":"10.1109\/CVPR.2008.4587635"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"crossref","unstructured":"Filip Radenovi\u0107 Giorgos Tolias and Ondvrej Chum. 2016. CNN Image Retrieval Learns from BoW: Unsupervised Fine-Tuning with Hard Examples ECCV.  Filip Radenovi\u0107 Giorgos Tolias and Ondvrej Chum. 2016. CNN Image Retrieval Learns from BoW: Unsupervised Fine-Tuning with Hard Examples ECCV.","DOI":"10.1007\/978-3-319-46448-0_1"},{"key":"e_1_3_2_1_32_1","unstructured":"Shaoqing Ren Kaiming He Ross Girshick and Jian Sun. 2015. Faster r-cnn: Towards real-time object detection with region proposal networks NIPS.   Shaoqing Ren Kaiming He Ross Girshick and Jian Sun. 2015. Faster r-cnn: Towards real-time object detection with region proposal networks NIPS."},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-015-0816-y"},{"volume-title":"Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556","year":"2014","author":"Simonyan Karen","key":"e_1_3_2_1_34_1"},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"crossref","unstructured":"Josef Sivic Andrew Zisserman and others. 2003. Video Google: a text retrieval approach to object matching in videos ICCV.   Josef Sivic Andrew Zisserman and others. 2003. Video Google: a text retrieval approach to object matching in videos ICCV.","DOI":"10.1109\/ICCV.2003.1238663"},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"crossref","unstructured":"Christian Szegedy Wei Liu Yangqing Jia Pierre Sermanet Scott Reed Dragomir Anguelov Dumitru Erhan Vincent Vanhoucke and Andrew Rabinovich. 2015. Going deeper with convolutions. In CVPR.  Christian Szegedy Wei Liu Yangqing Jia Pierre Sermanet Scott Reed Dragomir Anguelov Dumitru Erhan Vincent Vanhoucke and Andrew Rabinovich. 2015. Going deeper with convolutions. In CVPR.","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1145\/2812802"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2013.177"},{"key":"e_1_3_2_1_39_1","unstructured":"Giorgos Tolias Ronan Sicre and Herv\u00e9 J\u00e9gou. 2016. Particular object retrieval with integral max-pooling of CNN activations ICLR.  Giorgos Tolias Ronan Sicre and Herv\u00e9 J\u00e9gou. 2016. Particular object retrieval with integral max-pooling of CNN activations ICLR."},{"key":"e_1_3_2_1_40_1","unstructured":"Andrea Vedaldi and Brian Fulkerson. 2008. VLFeat: An Open and Portable Library of Computer Vision Algorithms. http:\/\/www.vlfeat.org\/ . (2008).  Andrea Vedaldi and Brian Fulkerson. 2008. VLFeat: An Open and Portable Library of Computer Vision Algorithms. http:\/\/www.vlfeat.org\/ . (2008)."},{"volume-title":"MatConvNet - Convolutional Neural Networks for MATLAB. CoRR","year":"2014","author":"Vedaldi Andrea","key":"e_1_3_2_1_41_1"},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1145\/2964284.2967252"},{"key":"e_1_3_2_1_43_1","unstructured":"Kai Yu and Tong Zhang. 2010. Improved Local Coordinate Coding using Local Tangents ICML.   Kai Yu and Tong Zhang. 2010. Improved Local Coordinate Coding using Local Tangents ICML."},{"volume-title":"Zeiler and Rob Fergus","year":"2013","author":"Matthew","key":"e_1_3_2_1_44_1"}],"event":{"name":"MM '17: ACM Multimedia Conference","sponsor":["SIGMM ACM Special Interest Group on Multimedia"],"location":"Mountain View California USA","acronym":"MM '17"},"container-title":["Proceedings of the 25th ACM international conference on Multimedia"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3123266.3123417","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3123266.3123417","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T02:14:03Z","timestamp":1750212843000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3123266.3123417"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,10,23]]},"references-count":44,"alternative-id":["10.1145\/3123266.3123417","10.1145\/3123266"],"URL":"https:\/\/doi.org\/10.1145\/3123266.3123417","relation":{},"subject":[],"published":{"date-parts":[[2017,10,23]]},"assertion":[{"value":"2017-10-23","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}