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We propose a novel single shot object detection network named Detection with Enriched Semantics (DES).
The pascal visual object classes (voc) challenge
M. Everingham, L. Van Gool, C. K. Williams, J. Winn, and A. Zisserman · 2010
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Understanding the difficulty of training deep feedforward neural networks
X. Glorot and Y. Bengio · 2010
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Imagenet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
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Overfeat: Integrated recognition, localization and detection using convolutional networks
P. Sermanet, D. Eigen, X. Zhang, M. Mathieu, R. Fergus, and Y. LeCun · 2013
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Selective search for object recognition
J. R. Uijlings, K. E. Van De Sande, T. Gevers, and A. W. Smeulders · 2013
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Rich feature hierarchies for accurate object detection and semantic segmentation
R. Girshick, J. Donahue, T. Darrell, and J. Malik · 2014
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Microsoft coco: Common objects in context
T.-Y. Lin, M. Maire, S. Belongie, J. Hays, P. Perona, D. Ramanan, P. Dollár, and C. L. Zitnick · 2014
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Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2014
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Edge boxes: Locating object proposals from edges
C. L. Zitnick and P. Dollár · 2014
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Object detection via a multi-region and semantic segmentation-aware cnn model
S. Gidaris and N. Komodakis · 2015
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Fast r-cnn
R. Girshick · 2015
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Fully convolutional networks for semantic segmentation
J. Long, E. Shelhamer, and T. Darrell · 2015
Cited alongside, same era.
Weakly-and semi-supervised learning of a deep convolutional network for semantic image segmentation
G. Papandreou, L.-C. Chen, K. P. Murphy, and A. L. Yuille · 2015
Cited alongside, same era.
Faster r-cnn: Towards real-time object detection with region proposal networks
S. Ren, K. He, R. Girshick, and J. Sun · 2015
Cited alongside, same era.
Inside-outside net: Detecting objects in context with skip pooling and recurrent neural networks
S. Bell, C. Lawrence Zitnick, K. Bala, and R. Girshick · 2016
Cited alongside, same era.
R-fcn: Object detection via region-based fully convolutional networks
J. Dai, Y. Li, K. He, and J. Sun · 2016
Contextual priming and feedback for faster r-cnn
A. Shrivastava and A. Gupta · 2016
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Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs
L.-C. Chen, G. Papandreou, I. Kokkinos, K. Murphy, and A. L. Yuille · 2017
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Dssd: Deconvolutional single shot detector
C.-Y. Fu, W. Liu, A. Ranga, A. Tyagi, and A. C. Berg · 2017
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Mask r-cnn
K. He, G. Gkioxari, P. Dollár, and R. Girshick · 2017
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Squeeze-and-excitation networks
J. Hu, L. Shen, and G. Sun · 2017
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Densely connected convolutional networks
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Cited alongside, same era.
Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
Cited alongside, same era.
Ssd: Single shot multibox detector
W. Liu, D. Anguelov, D. Erhan, C. Szegedy, S. Reed, C.-Y. Fu, and A. C. Berg · 2016
Cited alongside, same era.
You only look once: Unified, real-time object detection
J. Redmon, S. Divvala, R. Girshick, and A. Farhadi · 2016
Cited alongside, same era.
G. Huang, Z. Liu, L. van der Maaten, and K. Q. Weinberger · 2017
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Ron: Reverse connection with objectness prior networks for object detection
T. Kong, F. Sun, A. Yao, H. Liu, M. Lu, and Y. Chen · 2017
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Multiple instance detection network with online instance classifier refinement
P. Tang, X. Wang, X. Bai, and W. Liu · 2017
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Sort: Second-order response transform for visual recognition
Y. Wang, L. Xie, C. Liu, S. Qiao, Y. Zhang, W. Zhang, Q. Tian, and A. Yuille · 2017
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