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add focal loss paper to detection #90

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add focal loss paper to detection #90

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6 changes: 4 additions & 2 deletions README.md
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Expand Up @@ -98,6 +98,8 @@ Please feel free to [pull requests](https://github.com/kjw0612/awesome-deep-visi
* Wei Liu1, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, Alexander C. Berg, SSD: Single Shot MultiBox Detector, arXiv:1512.02325
* Speed/accuracy trade-offs for modern convolutional object detectors [[Paper]](https://arxiv.org/pdf/1611.10012v1.pdf)
* Jonathan Huang, Vivek Rathod, Chen Sun, Menglong Zhu, Anoop Korattikara, Alireza Fathi, Ian Fischer, Zbigniew Wojna, Yang Song, Sergio Guadarrama, Kevin Murphy, Google Research, arXiv:1611.10012
* Focal Loss for Dense Object Detection [[Paper]](https://arxiv.org/abs/1708.02002)
* Tsung-Yi Lin, Priya Goyal, Ross Girshick, Kaiming He, Piotr Dollár, Facebook AI Research (FAIR), arXiv:1708.02002

### Video Classification
* Nicolas Ballas, Li Yao, Pal Chris, Aaron Courville, "Delving Deeper into Convolutional Networks for Learning Video Representations", ICLR 2016. [[Paper](http://arxiv.org/pdf/1511.06432v4.pdf)]
Expand Down Expand Up @@ -347,7 +349,7 @@ Please feel free to [pull requests](https://github.com/kjw0612/awesome-deep-visi
* Convolutional / Recurrent Networks
* Aäron van den Oord, Nal Kalchbrenner, Oriol Vinyals, Lasse Espeholt, Alex Graves, Koray Kavukcuoglu. "Conditional Image Generation with PixelCNN Decoders"[[Paper]](https://arxiv.org/pdf/1606.05328v2.pdf)[[Code]](https://github.com/kundan2510/pixelCNN)
* Alexey Dosovitskiy, Jost Tobias Springenberg, Thomas Brox, "Learning to Generate Chairs with Convolutional Neural Networks", CVPR, 2015. [[Paper]](http://www.cv-foundation.org/openaccess/content_cvpr_2015/papers/Dosovitskiy_Learning_to_Generate_2015_CVPR_paper.pdf)
* Karol Gregor, Ivo Danihelka, Alex Graves, Danilo Jimenez Rezende, Daan Wierstra, "DRAW: A Recurrent Neural Network For Image Generation", ICML, 2015. [[Paper](https://arxiv.org/pdf/1502.04623v2.pdf)]
* Karol Gregor, Ivo Danihelka, Alex Graves, Danilo Jimenez Rezende, Daan Wierstra, "DRAW: A Recurrent Neural Network For Image Generation", ICML, 2015. [[Paper](https://arxiv.org/pdf/1502.04623v2.pdf)]
* Adversarial Networks
* Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, Yoshua Bengio, Generative Adversarial Networks, NIPS, 2014. [[Paper]](http://arxiv.org/abs/1406.2661)
* Emily Denton, Soumith Chintala, Arthur Szlam, Rob Fergus, Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks, NIPS, 2015. [[Paper]](http://arxiv.org/abs/1506.05751)
Expand Down Expand Up @@ -443,4 +445,4 @@ Please feel free to [pull requests](https://github.com/kjw0612/awesome-deep-visi
* [CVPR recap and where we're going@Zoya Bylinskii (MIT PhD Student)'s Blog](http://zoyathinks.blogspot.kr/2015/06/cvpr-recap-and-where-were-going.html)
* [Facebook's AI Painting@Wired](http://www.wired.com/2015/06/facebook-googles-fake-brains-spawn-new-visual-reality/)
* [Inceptionism: Going Deeper into Neural Networks@Google Research](http://googleresearch.blogspot.kr/2015/06/inceptionism-going-deeper-into-neural.html)
* [Implementing Neural networks](http://peterroelants.github.io/)
* [Implementing Neural networks](http://peterroelants.github.io/)