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A major challenge in scaling object detection is the difficulty of obtaining labeled images for large numbers of categories.
Distinctive image features from scale-invariant key points
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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Adapting SVM classifiers to data with shifted distributions
J. Yang, R. Yan, and A. Hauptmann · 2007
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Cross-domain video concept detection using adaptive svms
J. Yang, R. Yan, and A. G. Hauptmann · 2007
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A comparison of statistical significance tests for information retrieval evaluation
M. D. Smucker, J. Allan, and B. Carterette · 2007
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The pascal visual object classes (voc) challenge
M. Everingham, L. Van Gool, C. K. I. Williams, J. Winn, and A. Zisserman · 2010
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What you saw is not what you get: Domain adaptation using asymmetric kernel transforms
B. Kulis, K. Saenko, and T. Darrell · 2011
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Tabula rasa: Model transfer for object category detection
Y. Aytar and A. Zisserman · 2011
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Tabula rasa: Model transfer for object category detection
Y. Aytar and A. Zisserman · 2011
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ImageNet Large Scale Visual Recognition Challenge
A. Berg, J. Deng, and L. Fei-Fei · 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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Learning with augmented features for heterogeneous domain adaptation
L. Duan, D. Xu, and Ivor W. Tsang · 2012
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Enhancing exemplar svms using part level transfer regularization
Y. Aytar and A. Zisserman · 2012
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Diagnosing error in object detectors
D. Hoeim, Y. Chodpathumwan, and Q. Dai · 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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Efficient learning of domain-invariant image representations
J. Hoffman, E. Rodner, J. Donahue, K. Saenko, and T. Darrell · 2013
Confidence-rated multiple instance boosting for object detection
K. Ali and K. Saenko · 2014
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On learning to localize objects with minimal supervision
H. Song, R. Girshick, S. Jegelka, J. Mairal, Z. Harchaoui, and T. Darrell · 2014
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DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition
J. Donahue, Y. Jia, O. Vinyals, J. Hoffman, N. Zhang, E. Tzeng, and T. Darrell · 2014
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Descriptor matching with convolutional neural networks: a comparison to sift
Philipp Fischer, Alexey Dosovitskiy, and Thomas Brox · 2014
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Domain adaptation of deformable part-based models
J. Xu, S. Ramos, D. Vázquez, and A.M. López · 2014
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Interactive adaptation of real-time object detectors
D. Goehring, J. Hoffman, E. Rodner, K. Saenko, and T. Darrell · 2014
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Semi-supervised domain adaptation with instance constraints
J. Donahue, J. Hoffman, E. Rodner, K. Saenko, and T. Darrell · 2013
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Selective search for object recognition
J.R.R. Uijlings, K.E.A. van de Sande, T. Gevers, and A.W.M. 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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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
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Geodesic object proposals
P. Krähenbühl and V. Koltun · 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
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