{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,27]],"date-time":"2025-07-27T07:55:56Z","timestamp":1753602956384,"version":"3.37.3"},"reference-count":50,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2021,4,3]],"date-time":"2021-04-03T00:00:00Z","timestamp":1617408000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,4,3]],"date-time":"2021-04-03T00:00:00Z","timestamp":1617408000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"name":"Project of Educational Commission of Guangdong province of China","award":["2018KCXTD019"],"award-info":[{"award-number":["2018KCXTD019"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61976060"],"award-info":[{"award-number":["61976060"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Process Lett"],"published-print":{"date-parts":[[2021,6]]},"DOI":"10.1007\/s11063-021-10502-0","type":"journal-article","created":{"date-parts":[[2021,4,3]],"date-time":"2021-04-03T12:02:21Z","timestamp":1617451341000},"page":"2129-2145","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["A Comprehensive Study on VLAD"],"prefix":"10.1007","volume":"53","author":[{"given":"Xin","family":"Li","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8494-0504","authenticated-orcid":false,"given":"Lei","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhiping","family":"Jian","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Liyun","family":"Zuo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,4,3]]},"reference":[{"issue":"3","key":"10502_CR1","first-page":"57","volume":"4","author":"S Fekriershad","year":"2012","unstructured":"Fekriershad S, Saberi M, Tajeripour F (2012) An innovative skin detection approach using color based image retrieval technique. Int J Multimed Appl 4(3):57\u201365","journal-title":"Int J Multimed Appl"},{"issue":"3","key":"10502_CR2","doi-asserted-by":"publisher","first-page":"381","DOI":"10.1109\/TCYB.2014.2326596","volume":"45","author":"S Yan","year":"2015","unstructured":"Yan S, Xu X, Xu D, Lin S, Li X (2015) Image classification with densely sampled image windows and generalized adaptive multiple kernel learning. IEEE Trans Cybern 45(3):381\u2013390","journal-title":"IEEE Trans Cybern"},{"issue":"12","key":"10502_CR3","doi-asserted-by":"publisher","first-page":"2431","DOI":"10.1109\/TCYB.2014.2307862","volume":"44","author":"J Yu","year":"2014","unstructured":"Yu J, Rui Y, Tang Y, Tao D (2014) High-order distance-based multiview stochastic learning in image classification. IEEE Trans Cybern 44(12):2431\u20132442","journal-title":"IEEE Trans Cybern"},{"issue":"2","key":"10502_CR4","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1023\/B:VISI.0000029664.99615.94","volume":"60","author":"DG Lowe","year":"2004","unstructured":"Lowe DG (2004) Distinctive image features from scale-invariant keypoints. Int Conf Comput Vision 60(2):91\u2013110","journal-title":"Int Conf Comput Vision"},{"issue":"4","key":"10502_CR5","doi-asserted-by":"publisher","first-page":"591","DOI":"10.1109\/TPAMI.2008.111","volume":"31","author":"J Sivic","year":"2009","unstructured":"Sivic J, Zisserman A (2009) Efficient visual search of videos cast as text retrieval. IEEE Trans Pattern Anal Mach Intell 31(4):591\u2013606","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"2","key":"10502_CR6","doi-asserted-by":"publisher","first-page":"410","DOI":"10.1109\/TCYB.2015.2402751","volume":"46","author":"J Tang","year":"2016","unstructured":"Tang J, Shao L, Li X, Lu K (2016) A local structural descriptor for image matching via normalized graph laplacian embedding. IEEE Trans Cybern 46(2):410\u2013420","journal-title":"IEEE Trans Cybern"},{"key":"10502_CR7","doi-asserted-by":"crossref","unstructured":"Boureau Y.-L, Bach F, LeCun Y, Ponce J (2010) Learning mid-level features for recognition, In: IEEE Conference on computer vision and pattern recognition, IEEE, pp. 2559\u20132566","DOI":"10.1109\/CVPR.2010.5539963"},{"key":"10502_CR8","doi-asserted-by":"crossref","unstructured":"J\u00e9gou H, Douze M, Schmid C, P\u00e9rez P (2010) Aggregating local descriptors into a compact image representation, In: IEEE Conference on computer vision and pattern recognition, IEEE, pp. 3304\u20133311","DOI":"10.1109\/CVPR.2010.5540039"},{"issue":"9","key":"10502_CR9","doi-asserted-by":"publisher","first-page":"1704","DOI":"10.1109\/TPAMI.2011.235","volume":"34","author":"H Jegou","year":"2012","unstructured":"Jegou H, Perronnin F, Douze M, Sanchez J (2012) Aggregating local image descriptors into compact codes. IEEE Trans Pattern Anal Mach Intell 34(9):1704\u20131716","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"10502_CR10","doi-asserted-by":"crossref","unstructured":"Gong Y, Wang L, Guo R, Lazebnik S (2014) Multi-scale orderless pooling of deep convolutional activation features, In: European Conference on Computer Vision, Springer, pp. 392\u2013407","DOI":"10.1007\/978-3-319-10584-0_26"},{"key":"10502_CR11","doi-asserted-by":"crossref","unstructured":"Cimpoi M, Maji S, Kokkinos I, Mohamed S, Vedaldi A (2014) Describing textures in the wild, In: IEEE Conference on computer vision and pattern recognition, IEEE, pp. 3606\u20133613","DOI":"10.1109\/CVPR.2014.461"},{"key":"10502_CR12","doi-asserted-by":"crossref","unstructured":"Kantorov V, Laptev I (2014) Efficient feature extraction, encoding and classification for action recognition, In: IEEE Conference on computer vision and pattern recognition, IEEE, pp. 1\u20138","DOI":"10.1109\/CVPR.2014.332"},{"issue":"6","key":"10502_CR13","doi-asserted-by":"publisher","first-page":"1713","DOI":"10.1109\/TMM.2014.2329648","volume":"16","author":"E Spyromitros-Xioufis","year":"2014","unstructured":"Spyromitros-Xioufis E, Papadopoulos S, Kompatsiaris IY, Tsoumakas G, Vlahavas I (2014) A comprehensive study over vlad and product quantization in large-scale image retrieval. IEEE Trans Multimed 16(6):1713\u20131728","journal-title":"IEEE Trans Multimed"},{"key":"10502_CR14","doi-asserted-by":"crossref","unstructured":"Faraki M, Harandi M, Porikli F (2015) More about vlad: A leap from euclidean to riemannian manifolds, In: IEEE Conference on computer vision and pattern recognition, pp. 4951\u20134960","DOI":"10.1109\/CVPR.2015.7299129"},{"key":"10502_CR15","doi-asserted-by":"crossref","unstructured":"Perronnin F, Sanchez J, Mensink T (2010) Improving the fisher kernel for large-scale image classification, In: European Conference on computer vision, pp. 143-156","DOI":"10.1007\/978-3-642-15561-1_11"},{"key":"10502_CR16","doi-asserted-by":"publisher","first-page":"1783","DOI":"10.1109\/TPAMI.2016.2613873","volume":"99","author":"SS Husain","year":"2017","unstructured":"Husain SS, Bober M (2017) Improving large-scale image retrieval through robust aggregation of local descriptors. IEEE Trans Pattern Anal Mach Intell 99:1783\u20131796","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"10502_CR17","doi-asserted-by":"crossref","unstructured":"Delhumeau J, Gosselin P.-H, J\u00e9gou H, P\u00e9rez P (2013) Revisiting the vlad image representation, In: ACM international conference on multimedia, ACM, pp. 653\u2013656","DOI":"10.1145\/2502081.2502171"},{"key":"10502_CR18","doi-asserted-by":"crossref","unstructured":"Arandjelovic R, Zisserman A (2013) All about vlad, In: IEEE Conference on computer vision and pattern recognition, IEEE, pp. 1578-1585","DOI":"10.1109\/CVPR.2013.207"},{"key":"10502_CR19","doi-asserted-by":"crossref","unstructured":"Tolias G, Avrithis Y, J\u00e9gou H (2013) To aggregate or not to aggregate: Selective match kernels for image search, In: IEEE International Conference on computer vision, IEEE, pp. 1401\u20131408","DOI":"10.1109\/ICCV.2013.177"},{"key":"10502_CR20","doi-asserted-by":"crossref","unstructured":"Jegou H, Douze M, Schmid C (2008) Hamming embedding and weak geometric consistency for large scale image search, In: European Conference on computer vision, Springer, pp. 304\u2013317","DOI":"10.1007\/978-3-540-88682-2_24"},{"issue":"3","key":"10502_CR21","doi-asserted-by":"publisher","first-page":"316","DOI":"10.1007\/s11263-009-0285-2","volume":"87","author":"H J\u00e9gou","year":"2010","unstructured":"J\u00e9gou H, Douze M, Schmid C (2010) Improving bag-of-features for large scale image search. Int J Comput Vision 87(3):316\u2013336","journal-title":"Int J Comput Vision"},{"key":"10502_CR22","unstructured":"Angelina Uy. Mikaela, Lee Gim Hee (2018) PointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place Recognition, In: IEEE Conference on computer vision and pattern recognition, pp. 4470-4479"},{"key":"10502_CR23","unstructured":"Qi C. R, Su H, Mo K, Guibas L. J (2017) Pointnet: Deep learning on point sets for 3d classification and segmentation, In: IEEE Conference on computer vision and pattern recognition, IEEE, pp. 652-660"},{"key":"10502_CR24","doi-asserted-by":"crossref","unstructured":"Arandjelovic R, Gronat P, Torii A, Pajdla T, Sivic J (2016) NetVLAD: CNN architecture for weakly supervised place recognition. In: IEEE Conference on computer vision and pattern recognition, IEEE, pp. 5297-5307","DOI":"10.1109\/CVPR.2016.572"},{"key":"10502_CR25","first-page":"95","volume-title":"Convolution kernels on discrete structures, Technical report 7","author":"D Haussler","year":"1999","unstructured":"Haussler D (1999) Convolution kernels on discrete structures, Technical report 7. University of California at Santa Cruz, Department of Computer Science, pp 95\u2013174"},{"key":"10502_CR26","first-page":"725","volume":"8","author":"K Grauman","year":"2007","unstructured":"Grauman K, Darrell T (2007) The pyramid match kernel: Efficient learning with sets of features. J Mach Learn Res 8:725\u2013760","journal-title":"J Mach Learn Res"},{"key":"10502_CR27","unstructured":"Bo L, Sminchisescu C (2009) Efficient match kernel between sets of features for visual recognition, In: Advances in neural information processing systems, pp. 135\u2013143"},{"key":"10502_CR28","doi-asserted-by":"crossref","unstructured":"Murray N, Perronnin F (2014) Generalized max pooling, In: IEEE Conference on computer vision and pattern recognition, pp. 2473\u20132480","DOI":"10.1109\/CVPR.2014.317"},{"key":"10502_CR29","unstructured":"Kondor R, Jebara T (2003) A kernel between sets of vectors, In: International conference on machine learning, pp. 361\u2013368"},{"key":"10502_CR30","doi-asserted-by":"crossref","unstructured":"Grauman K, Darrell T (2005) The pyramid match kernel: Discriminative classification with sets of image features, In: IEEE International Conference on computer vision, pp. 1458\u20131465","DOI":"10.1109\/ICCV.2005.239"},{"key":"10502_CR31","unstructured":"Lazebnik S, Schmid C, Ponce J (2006) Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories, In: IEEE Conference on computer vision and pattern recognition, pp. 2169\u20132178"},{"issue":"11","key":"10502_CR32","first-page":"1","volume":"9","author":"L Van der Maaten","year":"2008","unstructured":"Van der Maaten L, Hinton G (2008) Visualizing data using t-SNE. J Mach Learn Res 9(11):1\u201348","journal-title":"J Mach Learn Res"},{"key":"10502_CR33","unstructured":"Boureau Y.-L, Ponce J, LeCun Y (2010) A theoretical analysis of feature pooling in visual recognition, In: International Conference on machine learning, pp. 111\u2013118"},{"key":"10502_CR34","doi-asserted-by":"crossref","unstructured":"Boureau Y, Roux N.\u00a0L, Bach F, Ponce J, LeCun Y (2011) Ask the locals: multi-way local pooling for image recognition, In: International Conference on computer vision, IEEE, pp. 1\u20138","DOI":"10.1109\/ICCV.2011.6126555"},{"key":"10502_CR35","doi-asserted-by":"crossref","unstructured":"Arandjelovic R, Zisserman A (2012) Three things everyone should know to improve object retrieval, In: IEEE Conference on computer vision and pattern recognition, pp. 1\u20138","DOI":"10.1109\/CVPR.2012.6248018"},{"key":"10502_CR36","doi-asserted-by":"crossref","unstructured":"Douze M, J\u00e9gou H, Schmid C, P\u00e9rez P (2010) Compact video description for copy detection with precise temporal alignment, In: European Conference on computer vision, Springer, pp. 522\u2013535","DOI":"10.1007\/978-3-642-15549-9_38"},{"key":"10502_CR37","unstructured":"Zhang X, Li Z, Zhang L, Ma W.-Y, Shum H.-Y (2009) Efficient indexing for large scale visual search, In: IEEE 12th International conference on computer vision, pp. 1103\u20131110"},{"issue":"1","key":"10502_CR38","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1016\/j.cviu.2005.09.012","volume":"106","author":"L Fei-Fei","year":"2007","unstructured":"Fei-Fei L, Fergus R, Perona P (2007) Learning generative visual models from few training examples: An incremental bayesian approach tested on 101 object categories. Comput Vision Imag Underst 106(1):59\u201370","journal-title":"Comput Vision Imag Underst"},{"key":"10502_CR39","doi-asserted-by":"crossref","unstructured":"Yao B, Jiang X, Khosla A, Lin A.\u00a0L, Guibas L, Fei-Fei L (2011) Human action recognition by learning bases of action attributes and parts, In: IEEE International Conference on computer vision (ICCV), pp. 1331\u20131338","DOI":"10.1109\/ICCV.2011.6126386"},{"issue":"1","key":"10502_CR40","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1108\/SR-07-2016-0120","volume":"37","author":"S Fekriershad","year":"2017","unstructured":"Fekriershad S, Tajeripour F (2017) Color texture classification based on proposed impulse-noise resistant color local binary patterns and significant points selection algorithm. Sens Rev 37(1):33\u201342","journal-title":"Sens Rev"},{"key":"10502_CR41","doi-asserted-by":"crossref","unstructured":"Nowak E, Jurie F, Triggs B (2006) Sampling strategies for bag-of-features image classification, In: European conference on computer vision, Springer, pp. 490\u2013503","DOI":"10.1007\/11744085_38"},{"issue":"3","key":"10502_CR42","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1145\/1961189.1961199","volume":"2","author":"C-C Chang","year":"2011","unstructured":"Chang C-C, Lin C-J (2011) Libsvm: a library for support vector machines. ACM Trans Intell Syst Technol 2(3):27","journal-title":"ACM Trans Intell Syst Technol"},{"key":"10502_CR43","doi-asserted-by":"crossref","unstructured":"Wang J, Yang J, Yu K, Lv F, Huang T, Gong Y (2010) Locality-constrained linear coding for image classification, In: IEEE Conference on computer vision and pattern recognition, pp. 3360\u20133367","DOI":"10.1109\/CVPR.2010.5540018"},{"issue":"9","key":"10502_CR44","doi-asserted-by":"publisher","first-page":"1159","DOI":"10.1109\/LSP.2014.2298888","volume":"21","author":"Z Zuo","year":"2014","unstructured":"Zuo Z, Wang G (2014) Learning discriminative hierarchical features for object recognition. Signal Process Lett 21(9):1159\u20131163","journal-title":"Signal Process Lett"},{"key":"10502_CR45","doi-asserted-by":"crossref","unstructured":"Zhu F, Jiang Z, Shao L (2014) Submodular object recognition, In: IEEE Conference on computer vision and pattern recognition, pp. 2457\u20132464","DOI":"10.1109\/CVPR.2014.315"},{"issue":"10","key":"10502_CR46","doi-asserted-by":"publisher","first-page":"5533","DOI":"10.1007\/s11042-015-2524-6","volume":"75","author":"X Long","year":"2016","unstructured":"Long X, Lu H, Peng Y et al (2016) Image classification based on improved VLAD. Multimed Tools Appl 75(10):5533\u20135555","journal-title":"Multimed Tools Appl"},{"issue":"8","key":"10502_CR47","doi-asserted-by":"publisher","first-page":"3241","DOI":"10.1109\/TIP.2014.2328894","volume":"23","author":"L Zhang","year":"2014","unstructured":"Zhang L, Zhen X, Shao L (2014) Learning object-to-class kernels for scene classification. IEEE Trans Image Process 23(8):3241\u20133253","journal-title":"IEEE Trans Image Process"},{"key":"10502_CR48","doi-asserted-by":"crossref","unstructured":"Wang P, Wang J, Zeng G, Xu W, Zha H, Li S (2013) Supervised kernel descriptors for visual recognition, In: IEEE Conference on computer vision and pattern recognition, pp. 2858\u20132865","DOI":"10.1109\/CVPR.2013.368"},{"key":"10502_CR49","unstructured":"Bo L, Ren X, Fox D (2010) Kernel descriptors for visual recognition, In: Advances in neural information processing systems, pp. 244\u2013252"},{"key":"10502_CR50","first-page":"1","volume":"99","author":"Q Li","year":"2017","unstructured":"Li Q, Peng Q, Yan C (2017) Multiple VLAD encoding of CNNs for image classification. Comput Sci Eng 99:1\u20138","journal-title":"Comput Sci Eng"}],"container-title":["Neural Processing Letters"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11063-021-10502-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11063-021-10502-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11063-021-10502-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,8,25]],"date-time":"2021-08-25T15:25:19Z","timestamp":1629905119000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11063-021-10502-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,4,3]]},"references-count":50,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2021,6]]}},"alternative-id":["10502"],"URL":"https:\/\/doi.org\/10.1007\/s11063-021-10502-0","relation":{},"ISSN":["1370-4621","1573-773X"],"issn-type":[{"type":"print","value":"1370-4621"},{"type":"electronic","value":"1573-773X"}],"subject":[],"published":{"date-parts":[[2021,4,3]]},"assertion":[{"value":"21 March 2021","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 April 2021","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}