mirrors
/
awesome-cbir-papers
mirror of https://github.com/willard-yuan/awesome-cbir-papers.git
1
0
Fork 0
Code Issues Projects Releases Wiki Activity

Update README.md

pull/2/head
Yong Yuan 2016-12-19 23:49:56 +08:00 committed by GitHub
parent a7d40139e8
commit 19f381f1df
1 changed files with 19 additions and 18 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

37
README.md
View File

@ -4,54 +4,55 @@
#### Local Feature Based
1. [Object retrieval with large vocabularies and fast spatial matching](https://www.robots.ox.ac.uk/~vgg/publications/papers/philbin07.pdf)
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)
- [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)
#### Deep Learning Feature Based
1. [Deep Image Retrieval:Learning Global Representations for Image earch](https://arxiv.org/abs/1604.01325)
2. [Bags of Local Convolutional Features for Scalable Instance Search](https://arxiv.org/abs/1604.01325)
3. [Faster R-CNN Features for Instance Search](https://github.com/imatge-upc/retrieval-2016-deepvision)
- [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)
#### Plan to read
1. [Visual Search at Pinterest]()
2. [VisualRank: Applying PageRank to Large-Scale Image Search]()
- [Visual Search at Pinterest]()
- [VisualRank: Applying PageRank to Large-Scale Image Search]()
### Tutorials
1. [Recent Image Search Techniques](http://cvpr2016.thecvf.com/program/tutorials)
2. [Compact Features for Visual Search](http://cvpr2016.thecvf.com/program/tutorials)
- [Recent Image Search Techniques](http://cvpr2016.thecvf.com/program/tutorials)
- [Compact Features for Visual Search](http://cvpr2016.thecvf.com/program/tutorials)
## 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)
- [Loss Functions for Top-k Error: Analysis and Insights]() and [Top-k Multiclass SVM](), [code](https://github.com/mlapin/libsdca)
### Tutorials
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/)
- [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/)
## Logo Detection and Classification
### Papers
1. LOGO-Net: Large-scale Deep Logo Detection and Brand Recognition with Deep Region-based Convolutional Networks
- LOGO-Net: Large-scale Deep Logo Detection and Brand Recognition with Deep Region-based Convolutional Networks
## Object Detection and Recognition
### Papers
1. SSD: Single Shot MultiBox Detector [code](https://github.com/weiliu89/caffe/tree/ssd)
- SSD: Single Shot MultiBox Detector [code](https://github.com/weiliu89/caffe/tree/ssd)
## Video Classification
### 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/)
- [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/)