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## Awesome image retrieval papers
### Papers
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1. [Object retrieval with large vocabularies and fast spatial matching ](https://www.robots.ox.ac.uk/~vgg/publications/papers/philbin07.pdf )
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2. [Improving the Fisher Kernel for Large-Scale Image Classification ](https://www.robots.ox.ac.uk/~vgg/rg/papers/peronnin_etal_ECCV10.pdf )
3. [Visual Categorization with Bags of Keypoints ](http://www.cs.princeton.edu/courses/archive/fall09/cos429/papers/csurka-eccv-04.pdf )
4. [ORB: an efficient alternative to SIFT or SURF ](https://www.willowgarage.com/sites/default/files/orb_final.pdf )
5. [Object Recognition from Local Scale-Invariant Features ](http://www.cs.ubc.ca/~lowe/papers/iccv99.pdf )
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6. [Deep Image Retrieval:Learning global representations for image search]()
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#### Plan to read
1. [Visual Search at Pinterest]()
2. [VisualRank: Applying PageRank to Large-Scale Image Search]()
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### Tutorials
1. [Recent Image Search Techniques ](http://cvpr2016.thecvf.com/program/tutorials )
2. [Compact Features for Visual Search ](http://cvpr2016.thecvf.com/program/tutorials )
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## Awesome multiclass classification
### papers
1. [Loss Functions for Top-k Error: Analysis and Insights]() and [Top-k Multiclass SVM](), [code ](https://github.com/mlapin/libsdca )
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### Tutorials
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1. [Linear Classification ](http://cs231n.github.io/linear-classify/ ), [中文版 ](http://blog.csdn.net/elaine_bao/article/details/50519970 ), [demo ](http://vision.stanford.edu/teaching/cs231n/linear-classify-demo/ )
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## Logo Detection and Classification
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### Papers
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1. LOGO-Net: Large-scale Deep Logo Detection and Brand Recognition with Deep Region-based Convolutional Networks
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## Object Detection and Recognition
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### Papers
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1. SSD: Single Shot MultiBox Detector [code ](https://github.com/weiliu89/caffe/tree/ssd )
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## Video Classification
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### Papers
1. [Large-scale Video Classification with Convolutional Neural Networks ](vision.stanford.edu/pdf/karpathy14.pdf )
2. [Learning Spatiotemporal Features With 3D Convolutional Networks ](http://www.cv-foundation.org/openaccess/content_iccv_2015/papers/Tran_Learning_Spatiotemporal_Features_ICCV_2015_paper.pdf ), [code ](https://github.com/Lasagne/Recipes/blob/master/examples/Video%20features%20with%20C3D.ipynb ), [doc ](https://docs.google.com/document/d/1-QqZ3JHd76JfimY4QKqOojcEaf5g3JS0lNh-FHTxLag/edit ), [project ](http://vlg.cs.dartmouth.edu/c3d/ )
