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Current people detectors operate either by scanning an image in a sliding window fashion or by classifying a discrete set of proposals.
Long short-term memory
Sepp Hochreiter and Juergen Schmidhuber · 1997
Earlier work this paper cites.
Pedestrian detection in crowded scenes
B. Leibe, E. Seemann, and B. Schiele · 2005
Earlier work this paper cites.
Connectionist temporal classification: Labelling unsegmented sequence data with recurrent neural networks
A. Graves, S. Fernandez, F. Gomez, and J. Schmidhuber · 2006
Earlier work this paper cites.
On detection of multiple object instances using Hough transform
O. Barinova, V. Lempitsky, and P. Kohli · 2010
Earlier work this paper cites.
Recognition using visual phrases
A. Farhadi and M.A. Sadeghi · 2011
Earlier work this paper cites.
Detection and tracking of occluded people
Siyu Tang, Mykhaylo Andriluka, and Bernt Schiele · 2012
Cited alongside, same era.
Selective search for object recognition
J.R.R. Uijlings, K.E.A. van de Sande, T. Gevers, and A.W.M. Smeulders · 2013
Cited alongside, same era.
Caffe: Convolutional architecture for fast feature embedding
Yangqing Jia, Evan Shelhamer, Jeff Donahue, Sergey Karayev, Jonathan Long, Ross Girshick, Sergio Guadarrama, and Trevor Darrell · 2014
Cited alongside, same era.
Sequence to sequence learning with neural networks
Ilya Sutskever, Oriol Vinyals, and Quoc Le · 2014
Cited alongside, same era.
Going deeper with convolutions
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich · 2014
Cited alongside, same era.
Rich feature hierarchies for accurate object detection and semantic segmentation
Ross Girshick, Jeff Donahue, Trevor Darrell, and Jitendra Malik
Cited in the paper.
Deep visual-semantic alignments for generating image descriptions
Andrej Karpathy and Li Fei-Fei
Cited in the paper.
Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E. Hinton
Cited in the paper.
Learning to count objects in images
Victor Lempitsky and Andrew Zisserman
Cited in the paper.
Single-pedestrian detection aided by multi-pedestrian detection
W. Ouyang and X. Wang
Cited in the paper.
Overfeat: Integrated recognition, localization and detection using convolutional networks
Pierre Sermanet, David Eigen, Xiang Zhang, Michael Mathieu, Rob Fergus, and Yann LeCun
Cited in the paper.
Scalable, high-quality object detection
Christian Szegedy, Scott Reed, Dumitru Erhan, and Dragomir Anguelov · 2014
Later among the works it cites.
http://github.com/Russell91/NLPCaffe
NLPCaffe · 2015
Closest in time.
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
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An empirical evaluation of deep learning on highway driving
Brody Huval, Tao Wang, Sameep Tandon, Jeff Kiske, Will Song, Joel Pazhayampallil, Mykhaylo Andriluka, Pranav Rajpurkar, Toki Migimatsu, Royce Cheng-Yue, Fernando Mujica, Adam Coates, and Andrew Y. Ng · 2015
Closest in time.
Filtered channel features for pedestrian detection
S. Zhang, R. Benenson, and B. Schiele · 2015
Closest in time.
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