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Almost all of the current top-performing object detection networks employ region proposals to guide the search for object instances.
Distinctive image features from scale-invariant keypoints
D. G. Lowe · 2004
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Histograms of oriented gradients for human detection
N. Dalal and B. Triggs · 2005
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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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What is an object?
B. Alexe, T. Deselaers, and V. Ferrari · 2010
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Constrained parametric min-cuts for automatic object segmentation
J. Carreira and C. Sminchisescu · 2010
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Object detection with discriminatively trained part-based models
P. F. Felzenszwalb, R. B. Girshick, D. McAllester, and D. Ramanan · 2010
Earlier work this paper cites.
Segmentation as selective search for object recognition
K. E. Van de Sande, J. R. Uijlings, T. Gevers, and A. W. Smeulders · 2011
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Object detection using strongly-supervised deformable part models
H. Azizpour and I. Laptev · 2012
Earlier work this paper cites.
Imagenet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
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Category-independent object-level saliency detection
Y. Jia and M. Han · 2013
Earlier work this paper cites.
Occlusion patterns for object class detection
B. Pepikj, M. Stark, P. Gehler, and B. Schiele · 2013
Earlier work this paper cites.
Multiscale combinatorial grouping
P. Arbelaez, J. Pont-Tuset, J. Barron, F. Marques, and J. Malik · 2014
Earlier work this paper cites.
Bing: Binarized normed gradients for objectness estimation at 300fps
M.-M. Cheng, Z. Zhang, W.-Y. Lin, and P. Torr · 2014
Cited alongside, same era.
Fast feature pyramids for object detection
P. Dollár, R. Appel, S. Belongie, and P. Perona · 2014
Cited alongside, same era.
Scalable object detection using deep neural networks
D. Erhan, C. Szegedy, A. Toshev, and D. Anguelov · 2014
Cited alongside, same era.
Rich feature hierarchies for accurate object detection and semantic segmentation
R. Girshick, J. Donahue, T. Darrell, and J. Malik · 2014
Cited alongside, same era.
Spatial pyramid pooling in deep convolutional networks for visual recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2014
Cited alongside, same era.
Caffe: Convolutional architecture for fast feature embedding
Y. Jia, E. Shelhamer, J. Donahue, S. Karayev, J. Long, R. B. Girshick, S. Guadarrama, and T. Darrell · 2014
Fast r-cnn
R. Girshick · 2015
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Hypercolumns for object segmentation and fine-grained localization
B. Hariharan, P. Arbeláez, R. Girshick, and J. Malik · 2015
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What makes for effective detection proposals?
J. Hosang, R. Benenson, P. Dollár, and B. Schiele · 2015
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Online object tracking with proposal selection
Y. Hua, K. Alahari, and C. Schmid · 2015
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Deepbox: Learning objectness with convolutional networks
W. Kuo, B. Hariharan, and J. Malik · 2015
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Learning to combine mid-level cues for object proposal generation
T. Lee, S. Fidler, and S. Dickinson · 2015
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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.
Improving object detection with deep convolutional networks via bayesian optimization and structured prediction
Y. Zhang, K. Sohn, R. Villegas, G. Pan, and H. Lee · 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. M. A. Eslami, L. Van Gool, C. K. I. Williams, J. Winn, and A. Zisserman · 2015
Cited alongside, same era.
Deepproposal: Hunting objects by cascading deep convolutional layers
A. Ghodrati, M. Pedersoli, T. Tuytelaars, A. Diba, and L. V. Gool · 2015
Cited alongside, same era.
Object detection via a multi-region & semantic segmentation-aware cnn model
S. Gidaris and N. Komodakis · 2015
Cited alongside, same era.
Fully convolutional networks for semantic segmentation
J. Long, E. Shelhamer, and T. Darrell · 2015
Later among the works it cites.
You only look once: Unified, real-time object detection
J. Redmon, S. Divvala, R. Girshick, and A. Farhadi · 2015
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Faster r-cnn: Towards real-time object detection with region proposal networks
S. Ren, K. He, R. Girshick, and J. Sun · 2015
Later among the works it cites.
Object detection networks on convolutional feature maps
S. Ren, K. He, R. Girshick, X. Zhang, and J. Sun · 2015
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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, A. C. Berg, and L. Fei-Fei · 2015
Later among the works it cites.
Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2015
Later among the works it cites.