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@ -53,6 +53,7 @@ The main goal is collect classical and solid work of image retrieval in academia
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## Deep Learning Feature (Global Feature)
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- [Smooth-AP: Smoothing the Path Towards Large-Scale Image Retrieval](https://arxiv.org/pdf/2007.12163.pdf), ECCV 2020
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- [SOLAR: Second-Order Loss and Attention for Image Retrieval](https://arxiv.org/pdf/2001.08972.pdf), ECCV 2020.
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- [Unifying Deep Local and Global Features for Image Search](https://arxiv.org/abs/2001.05027), arxiv 2020.
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- [SOLAR: Second-Order Loss and Attention for Image Retrieval](https://arxiv.org/abs/2001.08972v2), arxiv 2020.
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## ANN search
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- [Accelerating Large-Scale Inference with Anisotropic Vector Quantization](https://arxiv.org/pdf/1908.10396.pdf), [blog](https://ai.googleblog.com/2020/07/announcing-scann-efficient-vector.html), [code](https://github.com/google-research/google-research/tree/master/scann), ICML 2020.
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- [Improving Approximate Nearest Neighbor Search through Learned Adaptive Early Termination](https://www.pdl.cmu.edu/PDL-FTP/BigLearning/mod0246-liA.pdf), SIGMOD 2020.
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- [RobustiQ A Robust ANN Search Method for Billion-scale Similarity Search on GPUs](http://users.monash.edu/~yli/assets/pdf/icmr19-sigconf.pdf), ICMR 2019.
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- [Zoom: Multi-View Vector Search for Optimizing Accuracy, Latency and Memory](https://www.microsoft.com/en-us/research/uploads/prod/2018/08/zoom-multi-view-tech-report.pdf)
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