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The ImageNet Large Scale Visual Recognition Challenge is a benchmark in object category classification and detection on hundreds of object categories and millions of images.
Wordnet: A lexical database for english
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Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., and Fei-Fei, L. (2009) · 2009
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Decomposing a scene into geometric and semantically consistent regions
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Object detection using a max-margin hough transform
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Linear spatial pyramid matching using sparse coding for image classification
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The Pascal Visual Object Classes (VOC) challenge
Everingham, M., Van Gool, L., Williams, C. K. I., Winn, J., and Zisserman, A. (2010) · 2010
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Object detection with discriminatively trained part based models
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Locality-constrained Linear Coding for image classification
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The multidimensional wisdom of crowds
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Image classification using super-vector coding of local image descriptors
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Contour detection and hierarchical image segmentation
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Novel dataset for fine-grained image categorization
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Nonparametric scene parsing via label transfer
Liu, C., Yuen, J., and Torralba, A. (2011) · 2011
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High-dim. signature compression for large-scale image classification
Sanchez, J. and Perronnin, F. (2011) · 2011
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Torralba, A. and Efros, A. A. (2011) · 2011
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Caffe: An open source convolutional architecture for fast feature embedding
Jia, Y. (2013) · 2013
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Prime Object Proposals with Randomized Prim’s Algorithm
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Efficient estimation of word representations in vector space
Mikolov, T., Chen, K., Corrado, G., and Dean, J. (2013) · 2013
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From large scale image categorization to entry-level categories
Ordonez, V., Deng, J., Choi, Y., Berg, A. C., and Berg, T. L. (2013) · 2013
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Joint deep learning for pedestrian detection
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Detecting avocados to zucchinis: what have we done, and where are we going?
Russakovsky, O., Deng, J., Huang, Z., Berg, A., and Fei-Fei, L. (2013) · 2013
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Quality assessment for crowdsourced object annotations
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Adaptive deconvolutional networks for mid and high level feature learning
Zeiler, M. D., Taylor, G. W., and Fergus, R. (2011) · 2011
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Measuring the objectness of image windows
Alexe, B., Deselares, T., and Ferrari, V. (2012) · 2012
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Three things everyone should know to improve object retrieval
Arandjelovic, R. and Zisserman, A. (2012) · 2012
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Exact acceleration of linear object detectors
Dubout, C. and Fleuret, F. (2012) · 2012
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PASCAL Visual Object Classes Challenge (VOC)
Everingham, M., Gool, L. V., Williams, C., Winn, J., and Zisserman, A. (2005-2012) · 2012
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Overfeat: Integrated recognition, localization and detection using convolutional networks
Sermanet, P., Eigen, D., Zhang, X., Mathieu, M., Fergus, R., and LeCun, Y. (2013) · 2013
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Deep fisher networks for large-scale image classification
Simonyan, K., Vedaldi, A., and Zisserman, A. (2013) · 2013
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Deep learning using support vector machines
Tang, Y. (2013) · 2013
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Selective search for object recognition
Uijlings, J., van de Sande, K., Gevers, T., and Smeulders, A. (2013) · 2013
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Regularization of neural networks using dropconnect
Wan, L., Zeiler, M., Zhang, S., LeCun, Y., and Fergus, R. (2013) · 2013
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Regionlets for generic object detection
Wang, X., Yang, M., Zhu, S., and Lin, Y. (2013) · 2013
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Visualizing and understanding convolutional networks
Zeiler, M. D. and Fergus, R. (2013) · 2013
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Multiscale combinatorial grouping
Arbeláez, P., Pont-Tuset, J., Barron, J., Marques, F., and Malik, J. (2014) · 2014
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Scalable multi-label annotation
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The Pascal Visual Object Classes (VOC) challenge - a Retrospective
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Rich feature hierarchies for accurate object detection and semantic segmentation
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Deepid-net: multi-stage and deformable deep convolutional neural networks for object detection
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Deep epitomic convolutional neural networks
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Modeling image patches with a generic dictionary of mini-epitomes
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Reconstruction meets recognition challenge
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