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In the large-scale image retrieval task, the two most important requirements are the discriminability of image representations and the efficiency in computation and storage of representations.
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Hervé Jégou and Andrew Zisserman. 2014 · 2014
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Karen Simonyan and Andrew Zisserman. 2014 · 2014
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MatConvNet - Convolutional Neural Networks for MATLAB
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Aggregating Local Deep Features for Image Retrieval. In ICCV
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Compact Representation of High-Dimensional Feature Vectors for Large-Scale Image Recognition and Retrieval
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SIFT Meets CNN: A Decade Survey of Instance Retrieval
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Simultaneous Feature Aggregating and Hashing for Large-Scale Image Search. In CVPR
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Large-Scale Image Retrieval with Attentive Deep Local Features. In ICCV
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A Survey on Learning to Hash
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Selective Convolutional Descriptor Aggregation for Fine-Grained Image Retrieval
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Embedding based on function approximation for large scale image search
Thanh-Toan Do and Ngai-Man Cheung. 2018 · 2018
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Simultaneous Compression and Quantization: A Joint Approach for Efficient Unsupervised Hashing
Tuan Hoang, Thanh-Toan Do, Huu Le, Dang-Khoa Le Tan, and Ngai-Man Cheung. 2018 · 2018
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Quantization-based hashing: a general framework for scalable image and video retrieval
Jingkuan Song, Lianli Gao, Li Liu, Xiaofeng Zhu, and Nicu Sebe. 2018a · 2018
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Deep Region Hashing for Efficient Large-scale Instance Search from Images
Jingkuan Song, Tao He, Lianli Gao, Xing Xu, and Heng Tao Shen. 2018b · 2018
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Self-Supervised Video Hashing With Hierarchical Binary Auto-Encoder
J. Song, H. Zhang, X. Li, L. Gao, M. Wang, and R. Hong. 2018d · 2018
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Unsupervised Part-Based Weighting Aggregation of Deep Convolutional Features for Image Retrieval. In AAAI
Jian Xu, Cunzhao Shi, Chengzuo Qi, Chunheng Wang, and Baihua Xiao. 2018 · 2018
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Binary Constrained Deep Hashing Network for Image Retrieval without Manual Annotation. In WACV
Thanh-Toan Do, Tuan Hoang, Dang-Khoa Le-Tan, Trung Pham, Huu Le, Ngai-Man Cheung, and Ian Reid. 2019 · 2019
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