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Recent works in deep-learning have shown that second-order information is beneficial in many computer-vision tasks.
Sivic, J., Zisserman, A.: Video Google: A text retrieval approach to object matching in videos. In: ICCV (2003)
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Lowe, D.G.: Distinctive image features from scale-invariant keypoints. In: IJCV (2004)
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Bay, H., Tuytelaars, T., Van Gool, L.: SURF: Speeded up robust features. In: ECCV (2006)
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Nistér, D., Stewénius, H.: Scalable recognition with a vocabulary tree. In: CVPR (2006)
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Mikolajczyk, K., Matas, J.: Improving descriptors for fast tree matching by optimal linear projection. In: ICCV (2007)
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Philbin, J., Chum, O., Isard, M., Sivic, J., Zisserman, A.: Object retrieval with large vocabularies and fast spatial matching. In: CVPR (2007)
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Winder, S.A., Brown, M.: Learning local image descriptors. In: CVPR (2007)
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Jégou, H., Douze, M., Schmid, C.: Hamming embedding and weak geometry consistency for large scale image search. In: ECCV (2008)
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Philbin, J., Chum, O., Isard, M., Sivic, J., Zisserman, A.: Lost in quantization: Improving particular object retrieval in large scale image databases. In: CVPR (2008)
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Deng, J., Dong, W., Socher, R., Li, L.J., Li, K., Li, F.F.: ImageNet: A large-scale hierarchical image database. In: CVPR (2009)
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Jégou, H., Douze, M., Schmid, C., Pérez, P.: Aggregating local descriptors into a compact image representation. In: CVPR (2010)
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Perronnin, F., Liu, Y., , Sánchez, J., Poirier, H.: Large-scale image retrieval with compressed fisher vectors. In: CVPR (2010)
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Perronnin, F., Sánchez, J., Mensink, T.: Improving the fisher kernel for large-scale image classification. In: ECCV (2010)
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Chen, D.M., Baatz, G., Köeser, K., Tsai, S.S., Vedantham, R., Pylvänäinen, T., Roimela, K., Chen, X., Bach, J., Pollefeys, M., Girod, B., Grzeszczuk, R.: City-scale landmark identification on mobile devices. In: CVPR (2011)
2011
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Arandjelović, R., Zisserman, A.: Three things everyone should know to improve object retrieval. In: CVPR (2012)
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Carreira, J., Batista, J., Sminchisescu, C.: Semantic segmentation with second-order pooling. In: In ECCV (2012)
2012
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Jégou, H., Chum, O.: Negative evidences and co-occurrences in image retrieval: the benefit of PCA and whitening. In: ECCV (2012)
2012
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Jégou, H., Perronnin, F., Douze, M., Sánchez, J., Pérez, P., Schmid, C.: Aggregating local images descriptors into compact codes. TPAMI (2012)
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Krizhevsky, A., Sutskever, I., Hinton, G.E.: ImageNet classification with deep convolutional neural networks. In: NeurIPS (2012)
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Tolias, G., Avrithis, Y., Jégou, H.: To aggregate or not to aggregate: Selective match kernels for image search. In: ICCV (2013)
2013
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Arandjelović, R., Zisserman, A.: DisLocation: Scalable descriptor distinctiveness for location recognition. In: ACCV (2014)
2014
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Babenko, A., Slesarev, A., Chigorin, A., Lempitsky, V.: Neural codes for image retrieval. In: ECCV (2014)
2014
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Gong, Y., Wang, L., Guo, R., Lazebnik, S.: Multi-scale orderless pooling of deep convolutional activation features. In: ECCV (2014)
2014
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Sydorov, V., Sakurada, M., Lampert, C.H.: Deep fisher kernels – end to end learning of the fisher kernel GMM parameters. In: CVPR (2014)
2014
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Tolias, G., Furon, T., Jégou, H.: Orientation covariant aggregation of local descriptors with embeddings. In: ECCV (2014)
2014
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Yi, K.M., Trulls, E., Lepetit, V., Fua, P.: LIFT: Learned invariant feature transform. In: ECCV (2016)
2016
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Balntas, V., Lenc, K., Vedaldi, A., Mikolajczyk, K.: Hpatches: A benchmark and evaluation of handcrafted and learned local descriptors. In: CVPR (2017)
2017
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Mishchuk, A., Mishkin, D., Radenović, F., Matas, J.: Working hard to know your neighbor’s margins: Local descriptor learning loss. In: NeurIPS (2017)
2017
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Noh, H., Araujo, A., Sim, J., Weyand, T., Han, B.: Image retrieval with deep local features and attention-based keypoints. In: ICCV (2017)
2017
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Tian, Y., Fan, B., Wu, F.: L2-Net: Deep learning of discriminative patch descriptor in euclidean space. In: CVPR (2017)
2017
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Babenko, A., Lempitsky, V.: Aggregating deep convolutional features for image retrieval. In: ICCV (2015)
2015
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Kingma, D.P., Ba, J.: Adam: A method for stochastic optimization. In: ICLR (2015)
2015
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Lin, T., RoyChowdhury, A., Maji, S.: Bilinear CNN models for fine-grained visual recognition. In: ICCV (2015)
2015
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Ng, J.Y.H., Yang, F., Davis, L.S.: Exploiting local features from deep networks for image retrieval. In: CVPR Workshops (2015)
2015
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Ren, S., He, K., Girshick, R., Sun, J.: Faster R-CNN: Towards real-time object detection with region proposal networks. In: NeurIPS (2015)
2015
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Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. In: ICLR (2015)
2015
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Tolias, G., Avrithis, Y., Jégou, H.: Image search with selective match kernels: Aggregation across single and multiple images. In: IJCV (2015)
2015
Cited alongside, same era.
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, L., Polosukhin, I.: Attention is all you need. In: NeurIPS (2017)
2017
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Radenović, F., Iscen, A., Tolias, G., Avrithis, Y., Chum, O.: Revisiting oxford and paris: Large-scale image retrieval benchmarking. In: CVPR (2018)
2018
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Radenović, F., Tolias, G., Chum, O.: Fine-tuning CNN image retrieval with no human annotation. TPAMI (2018)
2018
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Wang, X., Girshick, R., Gupta, A., He, K.: Non-local neural networks. In: CVPR (2018)
2018
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Balntas, V., Lenc, K., Vedaldi, A., Tuytelaars, T., Matas, J., Mikolajczyk, K.: Hpatches: A benchmark and evaluation of handcrafted and learned local descriptors. TPAMI (2019)
2019
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Mukundan, A., Tolias, G., Chum, O.: Explicit spatial encoding for deep local descriptors. In: CVPR (2019)
2019
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Paszke, A., Gross, S., Massa, F., Lerer, A., Bradbury, J., Chanan, G., Killeen, T., Lin, Z., Gimelshein, N., Antiga, L., Desmaison, A., Kopf, A., Yang, E., DeVito, Z., Raison, M., Tejani, A., Chilamkurthy, S., Steiner, B., Fang, L., Bai, J., Chintala, S.: PyTorch: An imperative style, high-performance deep learning library. In: NeurIPS (2019)
2019
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Revaud, J., Almazán, J., Sampaio de Rezende, R., Roberto de Souza, C.: Learning with average precision: Training image retrieval with a listwise loss. In: ICCV (2019)
2019
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Teichmann, M., Araujo, A., Zhu, M., Sim, J.: Detect-to-Retrieve: Efficient regional aggregation for image search. In: CVPR (2019)
2019
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Tian, Y., Yu, X., Fan, B., Fuchao, W., Heijnen, H., Balntas, V.: SOSNet: Second order similarity regularization for local descriptor learning. In: CVPR (2019)
2019
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Xia, B.N., Gong, Y., Zhang, Y., Poellabauer, C.: Second-order non-local attention networks for person re-identification. In: ICCV (2019)
2019
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Yang, T.Y., Nguyen, D.K., Heijnen, H., Balntas, V.: DAME WEB: DynAmic MEan with Whitening Ensemble Binarization for landmark retrieval without human annotation. In: ICCV Workshops (2019)
2019
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Zhang, H., Goodfellow, I., Metaxas, D., Odena, A.: Self-attention generative adversarial networks. In: ICML (2019)
2019
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2019
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