awesome-cbir-papers/README.md

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## Awesome image retrieval papers
### Papers
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#### Local Feature Based
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- [Object retrieval with large vocabularies and fast spatial matching](https://www.robots.ox.ac.uk/~vgg/publications/papers/philbin07.pdf)
- [Improving the Fisher Kernel for Large-Scale Image Classification](https://www.robots.ox.ac.uk/~vgg/rg/papers/peronnin_etal_ECCV10.pdf)
- [Visual Categorization with Bags of Keypoints](http://www.cs.princeton.edu/courses/archive/fall09/cos429/papers/csurka-eccv-04.pdf)
- [ORB: an efficient alternative to SIFT or SURF](https://www.willowgarage.com/sites/default/files/orb_final.pdf)
- [Object Recognition from Local Scale-Invariant Features](http://www.cs.ubc.ca/~lowe/papers/iccv99.pdf)
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#### Deep Learning Feature Based
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- [Deep Image Retrieval:Learning Global Representations for Image earch](https://arxiv.org/abs/1604.01325)
- [Bags of Local Convolutional Features for Scalable Instance Search](https://arxiv.org/abs/1604.01325)
- [Faster R-CNN Features for Instance Search](https://github.com/imatge-upc/retrieval-2016-deepvision)
- [Cross-dimensional Weighting for Aggregated Deep Convolutional Features](https://arxiv.org/abs/1512.04065), [project](https://github.com/yahoo/crow)
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#### Plan to read
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- [Visual Search at Pinterest]()
- [VisualRank: Applying PageRank to Large-Scale Image Search]()
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### Tutorials
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- [Recent Image Search Techniques](http://cvpr2016.thecvf.com/program/tutorials)
- [Compact Features for Visual Search](http://cvpr2016.thecvf.com/program/tutorials)
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## Awesome multiclass classification
### papers
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- [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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- [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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- [LOGO-Net: Large-scale Deep Logo Detection and Brand Recognition with Deep Region-based Convolutional Networks](https://arxiv.org/abs/1511.02462)
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## Object Detection and Recognition
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### Papers
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- [SSD: Single Shot MultiBox Detector](www.cs.unc.edu/~wliu/papers/ssd.pdf), [code](https://github.com/weiliu89/caffe/tree/ssd)
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## Video Classification
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### Papers
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- [Large-scale Video Classification with Convolutional Neural Networks](vision.stanford.edu/pdf/karpathy14.pdf)
- [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/)