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@@ -73,21 +73,23 @@ Please feel free to [pull requests](https://github.com/kjw0612/awesome-deep-visi
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* Ross Girshick, Jeff Donahue, Trevor Darrell, Jitendra Malik, Rich feature hierarchies for accurate object detection and semantic segmentation, CVPR, 2014.
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* SPP, Microsoft Research [[Paper]](http://arxiv.org/pdf/1406.4729)
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* Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun, Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition, ECCV, 2014.
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-* Fast R-CNN, Microsoft Research [[Paper]] (http://arxiv.org/pdf/1504.08083)
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+* Fast R-CNN, Microsoft Research [[Paper]](http://arxiv.org/pdf/1504.08083)
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* Ross Girshick, Fast R-CNN, arXiv:1504.08083.
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-* Faster R-CNN, Microsoft Research [[Paper]] (http://arxiv.org/pdf/1506.01497)
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+* Faster R-CNN, Microsoft Research [[Paper]](http://arxiv.org/pdf/1506.01497)
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* Shaoqing Ren, Kaiming He, Ross Girshick, Jian Sun, Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks, arXiv:1506.01497.
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-* R-CNN minus R, Oxford [[Paper]] (http://arxiv.org/pdf/1506.06981)
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+* R-CNN minus R, Oxford [[Paper]](http://arxiv.org/pdf/1506.06981)
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* Karel Lenc, Andrea Vedaldi, R-CNN minus R, arXiv:1506.06981.
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-* End-to-end people detection in crowded scenes [[Paper]] (http://arxiv.org/abs/1506.04878)
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+* End-to-end people detection in crowded scenes [[Paper]](http://arxiv.org/abs/1506.04878)
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* Russell Stewart, Mykhaylo Andriluka, End-to-end people detection in crowded scenes, arXiv:1506.04878.
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-* You Only Look Once: Unified, Real-Time Object Detection [[Paper]] (http://arxiv.org/abs/1506.02640)
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+* You Only Look Once: Unified, Real-Time Object Detection [[Paper]](http://arxiv.org/abs/1506.02640)
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* Joseph Redmon, Santosh Divvala, Ross Girshick, Ali Farhadi, You Only Look Once: Unified, Real-Time Object Detection, arXiv:1506.02640
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* Inside-Outside Net [[Paper]](http://arxiv.org/abs/1512.04143)
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* Sean Bell, C. Lawrence Zitnick, Kavita Bala, Ross Girshick, Inside-Outside Net: Detecting Objects in Context with Skip Pooling and Recurrent Neural Networks
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* Deep Residual Network (Current State-of-the-Art) [[Paper]](http://arxiv.org/abs/1512.03385)
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* Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun, Deep Residual Learning for Image Recognition
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* Weakly Supervised Object Localization with Multi-fold Multiple Instance Learning [[Paper](http://arxiv.org/pdf/1503.00949.pdf)]
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+* R-FCN [[Paper]](https://arxiv.org/abs/1605.06409) [[Code]](https://github.com/daijifeng001/R-FCN)
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+ * Jifeng Dai, Yi Li, Kaiming He, Jian Sun, R-FCN: Object Detection via Region-based Fully Convolutional Networks
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### Video Classification
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* 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)]
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