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- [All about VLAD]()
- [Aggregating localdescriptors into a compact image representatio]()
- [More About VLAD: A Leap from Euclidean to Riemannian Manifolds]()
- [Hamming embedding and weak geometric consistency for large scale image search]()
- [Revisiting the VLAD image representation](https://hal.inria.fr/hal-00840653v1/document), [project](https://github.com/jorjasso/VLAD/blob/master/VLADlib/VLAD.py)
- [Improving the Fisher Kernel for Large-Scale Image Classification](https://www.robots.ox.ac.uk/~vgg/rg/papers/peronnin_etal_ECCV10.pdf)
- [Image Classification with the Fisher Vector: Theory and Practice](https://hal.inria.fr/hal-00830491/document)
- [Democratic Diffusion Aggregation for ImageRetrieval]()
- [A Vote-and-Verify Strategy for Fast Spatial Verification in Image Retrieval]()
- []()
#### Deep Learning Feature Based
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- [Selective Deep Convolutional Features for Image Retrieval](https://arxiv.org/pdf/1707.00809v1.pdf)
- [Class-Weighted Convolutional Features for Image Retrieval](https://github.com/imatge-upc/retrieval-2017-cam)
- [Towards Good Practices for Image Retrieval Based on CNN Features]()
- [Fine-tuning CNN Image Retrieval with No Human Annotation](https://arxiv.org/abs/1711.02512)
#### ANN search
- [Practical and Optimal LSH for Angular Distance](chrome-extension://ikhdkkncnoglghljlkmcimlnlhkeamad/pdf-viewer/web/viewer.html?file=http%3A%2F%2Fpapers.nips.cc%2Fpaper%2F5893-practical-and-optimal-lsh-for-angular-distance.pdf)
- [pq-fast-scan](https://github.com/technicolor-research/pq-fast-scan)
- [faiss](https://github.com/facebookresearch/faiss). A library for efficient similarity search and clustering of dense vectors.
- [Polysemous codes]()
- [lopq](https://github.com/yahoo/lopq). Training of Locally Optimized Product Quantization (LOPQ) models for approximate nearest neighbor search of high dimensional data in Python and Spark.
- [nns_benchmark](https://github.com/DBWangGroupUNSW/nns_benchmark). Benchmark of Nearest Neighbor Search on High Dimensional Data.
- [Optimized Product Quantization](http://kaiminghe.com/cvpr13/index.html)