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We present RON, an efficient and effective framework for generic object detection.
Distinctive image features from scale-invariant keypoints
D. G. Lowe · 2004
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An hog-lbp human detector with partial occlusion handling
X. Wang, T. X. Han, and S. Yan · 2009
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Object detection with discriminatively trained part-based models
P. F. Felzenszwalb, R. B. Girshick, D. McAllester, and D. Ramanan · 2010
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Object detection using strongly-supervised deformable part models
H. Azizpour and I. Laptev · 2012
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Diagnosing error in object detectors
D. Hoiem, Y. Chodpathumwan, and Q. Dai · 2012
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Imagenet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
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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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Multiscale combinatorial grouping
P. Arbelaez, J. Pont-Tuset, J. Barron, F. Marques, and J. Malik · 2014
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Fast feature pyramids for object detection
P. Dollár, R. Appel, S. Belongie, and P. Perona · 2014
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Scalable object detection using deep neural networks
D. Erhan, C. Szegedy, A. Toshev, and D. Anguelov · 2014
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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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Spatial pyramid pooling in deep convolutional networks for visual recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2014
Cited alongside, same era.
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
Cited alongside, same era.
Overfeat: Integrated recognition, localization and detection using convolutional networks
P. Sermanet, D. Eigen, X. Zhang, M. Mathieu, R. Fergus, and Y. LeCun · 2014
Cited alongside, same era.
Edge boxes: Locating object proposals from edges
C. L. Zitnick and P. Dollár · 2014
Cited alongside, same era.
The pascal visual object classes challenge: A retrospective
M. Everingham, S. A. Eslami, L. Van Gool, C. K. Williams, J. Winn, and A. Zisserman · 2015
Cited alongside, same era.
Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2015
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Going deeper with convolutions
C. Szegedy, W. Liu, Y. Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke, and A. Rabinovich · 2015
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Improving object detection with deep convolutional networks via bayesian optimization and structured prediction
Y. Zhang, K. Sohn, R. Villegas, G. Pan, and H. Lee · 2015
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Inside-outside net: Detecting objects in context with skip pooling and recurrent neural networks
S. Bell, C. L. Zitnick, K. Bala, and R. Girshick · 2016
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R-fcn: Object detection via region-based fully convolutional networks
J. Dai, Y. Li, K. He, and J. Sun · 2016
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Deep residual learning for image recognition
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S. Gidaris and N. Komodakis · 2015
Cited alongside, same era.
Fast r-cnn
R. Girshick · 2015
Cited alongside, same era.
Hypercolumns for object segmentation and fine-grained localization
B. Hariharan, P. Arbeláez, R. Girshick, and J. Malik · 2015
Cited alongside, same era.
Fully convolutional networks for semantic segmentation
J. Long, E. Shelhamer, and T. Darrell · 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.
Imagenet large scale visual recognition challenge
O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, Z. Huang, A. Karpathy, A. Khosla, M. Bernstein, et al · 2015
Cited alongside, same era.
K. He, X. Zhang, S. Ren, and J. Sun · 2016
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Hypernet: Towards accurate region proposal generation and joint object detection
T. Kong, A. Yao, Y. Chen, and F. Sun · 2016
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Ssd: Single shot multibox detector
W. Liu, D. Anguelov, D. Erhan, C. Szegedy, and S. Reed · 2016
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You only look once: Unified, real-time object detection
J. Redmon, S. Divvala, R. Girshick, and A. Farhadi · 2016
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Training region-based object detectors with online hard example mining
A. Shrivastava, A. Gupta, and R. Girshick · 2016
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