{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:23:42Z","timestamp":1750220622125,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":21,"publisher":"ACM","license":[{"start":{"date-parts":[[2020,10,12]],"date-time":"2020-10-12T00:00:00Z","timestamp":1602460800000},"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":[[2020,10,12]]},"DOI":"10.1145\/3394171.3414814","type":"proceedings-article","created":{"date-parts":[[2020,10,12]],"date-time":"2020-10-12T13:12:00Z","timestamp":1602508320000},"page":"4448-4452","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Reproducibility Companion Paper: 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"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Thanh-Toan","family":"Do","sequence":"additional","affiliation":[{"name":"University of Liverpool, Liverpool, United Kingdom"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ngai-Man","family":"Cheung","sequence":"additional","affiliation":[{"name":"Singapore University of Technology and Design, Singapore, Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michael","family":"Riegler","sequence":"additional","affiliation":[{"name":"SimulaMet, Oslo, Norway"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jan","family":"Zah\u00e1lka","sequence":"additional","affiliation":[{"name":"Czech Technical University in Prague, Prague, Czech Rep"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2020,10,12]]},"reference":[{"key":"e_1_3_2_2_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. In CVPR.  Relja Arandjelovi\u0107 Petr Gronat Akihiko Torii Tomas Pajdla and Josef Sivic. 2016. NetVLAD: CNN architecture for weakly supervised place recognition. In CVPR.","DOI":"10.1109\/CVPR.2016.572"},{"key":"e_1_3_2_2_2_1","unstructured":"Artem Babenko and Victor Lempitsky. 2015. Aggregating Local Deep Features for Image Retrieval. In ICCV.  Artem Babenko and Victor Lempitsky. 2015. Aggregating Local Deep Features for Image Retrieval. In ICCV."},{"key":"e_1_3_2_2_3_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_2_4_1","doi-asserted-by":"crossref","unstructured":"Jonathan Delhumeau Philippe-Henri Gosselin Herv\u00e9 J\u00e9gou and Patrick P\u00e9rez. 2013. Revisiting the VLAD image representation. In ACM MM.  Jonathan Delhumeau Philippe-Henri Gosselin Herv\u00e9 J\u00e9gou and Patrick P\u00e9rez. 2013. Revisiting the VLAD image representation. In ACM MM.","DOI":"10.1145\/2502081.2502171"},{"key":"e_1_3_2_2_5_1","volume-title":"Embedding based on function approximation for large scale image search. TPAMI","author":"Do Thanh-Toan","year":"2017","unstructured":"Thanh-Toan Do and Ngai-Man Cheung . 2017. Embedding based on function approximation for large scale image search. TPAMI ( 2017 ). Thanh-Toan Do and Ngai-Man Cheung. 2017. Embedding based on function approximation for large scale image search. TPAMI (2017)."},{"key":"e_1_3_2_2_6_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. In ECCV.  Albert Gordo Jon Almazan Jerome Revaud and Diane Larlus. 2016. Deep Image Retrieval: Learning Global Representations for Image Search. In ECCV.","DOI":"10.1007\/978-3-319-46466-4_15"},{"key":"e_1_3_2_2_7_1","volume-title":"Dang-Khoa Le Tan, and Ngai-Man Cheung","author":"Hoang Tuan","year":"2017","unstructured":"Tuan Hoang , Thanh-Toan Do , Dang-Khoa Le Tan, and Ngai-Man Cheung . 2017 . Selective Deep Convolutional Features for Image Retrieval. In ACM Multimedia 2017. Tuan Hoang, Thanh-Toan Do, Dang-Khoa Le Tan, and Ngai-Man Cheung. 2017. Selective Deep Convolutional Features for Image Retrieval. In ACM Multimedia 2017."},{"key":"e_1_3_2_2_8_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_2_9_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-009-0285-2"},{"key":"e_1_3_2_2_10_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. In CVPR.  Herv\u00e9 J\u00e9gou Matthijs Douze Cordelia Schmid and Patrick P\u00e9rez. 2010. Aggregating local descriptors into a compact image representation. In CVPR.","DOI":"10.1109\/CVPR.2010.5540039"},{"key":"e_1_3_2_2_11_1","doi-asserted-by":"crossref","unstructured":"Herv\u00e9 J\u00e9gou and Andrew Zisserman. 2014. Triangulation embedding and democratic aggregation for image search. In CVPR.  Herv\u00e9 J\u00e9gou and Andrew Zisserman. 2014. Triangulation embedding and democratic aggregation for image search. In CVPR.","DOI":"10.1109\/CVPR.2014.417"},{"key":"e_1_3_2_2_12_1","volume-title":"Cross-dimensional Weighting for Aggregated Deep Convolutional Features. In ECCV Workshops.","author":"Kalantidis Yannis","year":"2016","unstructured":"Yannis Kalantidis , Clayton Mellina , and Simon Osindero . 2016 . Cross-dimensional Weighting for Aggregated Deep Convolutional Features. In ECCV Workshops. Yannis Kalantidis, Clayton Mellina, and Simon Osindero. 2016. Cross-dimensional Weighting for Aggregated Deep Convolutional Features. In ECCV Workshops."},{"key":"e_1_3_2_2_13_1","unstructured":"Ying Li Xiangwei Kong Liang Zheng and Qi Tian. 2016. Exploiting Hierarchical Activations of Neural Network for Image Retrieval. In ACM MM.  Ying Li Xiangwei Kong Liang Zheng and Qi Tian. 2016. Exploiting Hierarchical Activations of Neural Network for Image Retrieval. In ACM MM."},{"key":"e_1_3_2_2_14_1","doi-asserted-by":"crossref","unstructured":"David G. Lowe. 1999. Object Recognition from Local Scale-Invariant Features. In ICCV.  David G. Lowe. 1999. Object Recognition from Local Scale-Invariant Features. In ICCV.","DOI":"10.1109\/ICCV.1999.790410"},{"key":"e_1_3_2_2_15_1","doi-asserted-by":"crossref","unstructured":"Florent Perronnin and Christopher Dance. 2007. Fisher Kernels on Visual Vocabularies for Image Categorization. In CVPR.  Florent Perronnin and Christopher Dance. 2007. Fisher Kernels on Visual Vocabularies for Image Categorization. In CVPR.","DOI":"10.1109\/CVPR.2007.383266"},{"key":"e_1_3_2_2_16_1","doi-asserted-by":"crossref","unstructured":"Florent Perronnin Jorge S\u00e1nchez and Thomas Mensink. 2010. Improving the fisher kernel for large-scale image classification. In ECCV.  Florent Perronnin Jorge S\u00e1nchez and Thomas Mensink. 2010. Improving the fisher kernel for large-scale image classification. In ECCV.","DOI":"10.1007\/978-3-642-15561-1_11"},{"key":"e_1_3_2_2_17_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. In CVPR.  James Philbin Ondrej Chum Michael Isard Josef Sivic and Andrew Zisserman. 2007. Object retrieval with large vocabularies and fast spatial matching. In CVPR.","DOI":"10.1109\/CVPR.2007.383172"},{"key":"e_1_3_2_2_18_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. In 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. In CVPR.","DOI":"10.1109\/CVPR.2008.4587635"},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"crossref","unstructured":"Filip Radenovi\u0107 Giorgos Tolias and Ondvr ej Chum. 2016. CNN Image Retrieval Learns from BoW: Unsupervised Fine-Tuning with Hard Examples. In ECCV.  Filip Radenovi\u0107 Giorgos Tolias and Ondvr ej Chum. 2016. CNN Image Retrieval Learns from BoW: Unsupervised Fine-Tuning with Hard Examples. In ECCV.","DOI":"10.1007\/978-3-319-46448-0_1"},{"key":"e_1_3_2_2_20_1","volume-title":"Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556","author":"Simonyan Karen","year":"2014","unstructured":"Karen Simonyan and Andrew Zisserman . 2014. Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556 ( 2014 ). Karen Simonyan and Andrew Zisserman. 2014. Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556 (2014)."},{"key":"e_1_3_2_2_21_1","unstructured":"Giorgos Tolias Ronan Sicre and Herv\u00e9 J\u00e9gou. 2016. Particular object retrieval with integral max-pooling of CNN activations. In ICLR.  Giorgos Tolias Ronan Sicre and Herv\u00e9 J\u00e9gou. 2016. Particular object retrieval with integral max-pooling of CNN activations. In ICLR."}],"event":{"name":"MM '20: The 28th ACM International Conference on Multimedia","sponsor":["SIGMM ACM Special Interest Group on Multimedia"],"location":"Seattle WA USA","acronym":"MM '20"},"container-title":["Proceedings of the 28th ACM International Conference on Multimedia"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3394171.3414814","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3394171.3414814","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T22:01:24Z","timestamp":1750197684000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3394171.3414814"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10,12]]},"references-count":21,"alternative-id":["10.1145\/3394171.3414814","10.1145\/3394171"],"URL":"https:\/\/doi.org\/10.1145\/3394171.3414814","relation":{},"subject":[],"published":{"date-parts":[[2020,10,12]]},"assertion":[{"value":"2020-10-12","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}