From 67076377a35d76a9677bc16a813d873101e28006 Mon Sep 17 00:00:00 2001 From: Jordan Peltier Date: Tue, 20 Feb 2018 13:59:30 +0100 Subject: [PATCH] add focal loss paper to detection --- README.md | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index a181ed0..0d644cc 100644 --- a/README.md +++ b/README.md @@ -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)] @@ -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) @@ -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/)