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Visual attributes are great means of describing images or scenes, in a way both humans and computers understand.
Handwritten digit recognition with a back-propagation network
LeCun, Y., Boser, B.E., Denker, J.S., Henderson, D., Howard, R.E., Hubbard, W.E., Jackel, L.D.: · 1989
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Modeling the shape of the scene: A holistic representation of the spatial envelope
Oliva, A., Torralba, A.: · 2001
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Optimizing search engines using clickthrough data
Joachims, T.: · 2002
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Histograms of oriented gradients for human detection
Dalal, N., Triggs, B.: · 2005
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Learning to rank using gradient descent
Burges, C., Shaked, T., Renshaw, E., Lazier, A., Deeds, M., Hamilton, N., Hullender, G.: · 2005
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SVM-KNN: Discriminative nearest neighbor classification for visual category recognition
Zhang, H., Berg, A., Maire, M., Malik, J.: · 2006
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Learning visual attributes
Ferrari, V., Zisserman, A.: · 2007
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Van der Maaten, L., Hinton, G.: · 2008
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Describing objects by their attributes
Farhadi, A., Endres, I., Hoiem, D., Forsyth, D.: · 2009
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Visual recognition with humans in the loop
Branson, S., Wah, C., Babenko, B., Schroff, F., Welinder, P., Perona, P., Belongie, S.: · 2010
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Every picture tells a story: Generating sentences from images
Farhadi, A., Hejrati, M., Sadeghi, M.A., Young, P., Rashtchian, C., Hockenmaier, J., Forsyth, D.A.: · 2010
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Understanding the difficulty of training deep feedforward neural networks
Glorot, X., Bengio, Y.: · 2010
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Relative attributes
Parikh, D., Grauman, K.: · 2011
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Recognizing human actions by attributes
Liu, J., Kuipers, B., Savarese, S.: · 2011
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Hierarchical ranking of facial attributes
Datta, A., Feris, R., Vaquero, D.: · 2011
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Whittlesearch: Image Search with Relative Attribute Feedback
Kovashka, A., Parikh, D., Grauman, K.: · 2012
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Imagenet classification with deep convolutional neural networks
Krizhevsky, A., Sutskever, I., Hinton, G.E.: · 2012
Cited alongside, same era.
Relative forest for attribute prediction
Li, S., Shan, S., Chen, X.: · 2012
Cited alongside, same era.
Lecture 6.5—RmsProp: Divide the gradient by a running average of its recent magnitude
Tieleman, T., Hinton, G.: · 2012
Cited alongside, same era.
Efficient large-scale structured learning
Branson, S., Beijbom, O., Belongie, S.: · 2013
Cited alongside, same era.
Deep inside convolutional networks: Visualising image classification models and saliency maps
Simonyan, K., Vedaldi, A., Zisserman, A.: · 2013
Cited alongside, same era.
Video event recognition using concept attributes
Liu, J., Yu, Q., Javed, O., Ali, S., Tamrakar, A., Divakaran, A., Cheng, H., Sawhney, H.: · 2013
Deep learning for content-based image retrieval: A comprehensive study
Wan, J., Wang, D., Hoi, S.C.H., Wu, P., Zhu, J., Zhang, Y., Li, J.: · 2014
Later among the works it cites.
Very deep convolutional networks for large-scale image recognition
Simonyan, K., Zisserman, A.: · 2014
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Relative parts: Distinctive parts for learning relative attributes
Sandeep, R.N., Verma, Y., Jawahar, C.V.: · 2014
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Fully convolutional networks for semantic segmentation
Long, J., Shelhamer, E., Darrell, T.: · 2015
Closest in time.
Attributes and categories for generic instance search from one example
Tao, R., Smeulders, A.W., Chang, S.F.: · 2015
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Just noticeable differences in visual attributes
Yu, A., Grauman, K.: · 2015
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Cited alongside, same era.
Attribute pivots for guiding relevance feedback in image search
Kovashka, A., Grauman, K.: · 2013
Cited alongside, same era.
Attribute-based classification for zero-shot visual object categorization
Lampert, C., Nickisch, H., Harmeling, S.: · 2014
Cited alongside, same era.
Rich feature hierarchies for accurate object detection and semantic segmentation
Girshick, R., Donahue, J., Darrell, T., Malik, J.: · 2014
Cited alongside, same era.
Cnn features off-the-shelf: an astounding baseline for recognition
Razavian, A.S., Azizpour, H., Sullivan, J., Carlsson, S.: · 2014
Cited alongside, same era.
Semantic pyramids for gender and action recognition
Khan, F., van de Weijer, J., Anwer, R., Felsberg, M., Gatta, C.: · 2014
Cited alongside, same era.
Decorrelating semantic visual attributes by resisting the urge to share
Jayaraman, D., Sha, F., Grauman, K.: · 2014
Cited alongside, same era.
Closest in time.
On the relationship between visual attributes and convolutional networks
Escorcia, V., Carlos Niebles, J., Ghanem, B.: · 2015
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Deep-carving: Discovering visual attributes by carving deep neural nets
Shankar, S., Garg, V.K., Cipolla, R.: · 2015
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Deep semantic pyramids for human attributes and action recognition
Khan, F.S., Anwer, R.M., van de Weijer, J., Felsberg, M., Laaksonen, J.: · 2015
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Cross-domain image retrieval with a dual attribute-aware ranking network
Huang, J., Feris, R.S., Chen, Q., Yan, S.: · 2015
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Going deeper with convolutions
Szegedy, C., Liu, W., Jia, Y., Sermanet, P., Reed, S., Anguelov, D., Erhan, D., Vanhoucke, V., Rabinovich, A.: · 2015
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Lasagne: First release. (2015)
Dieleman, S., Schlüter, J., Raffel, C., Olson, E., Sønderby, S.K., Nouri, D., Maturana, D., Thoma, M., Battenberg, E., Kelly, J., Fauw, J.D., Heilman, M., diogo149, McFee, B., Weideman, H., takacsg84, peterderivaz, Jon, instagibbs, Rasul, D.K., CongLiu, Britefury, Degrave, J.: · 2015
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Imagenet large scale visual recognition challenge
Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., Huang, Z., Karpathy, A., Khosla, A., Bernstein, M., et al.: · 2015
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Exploring locally rigid discriminative patches for learning relative attributes
Verma, Y., Jawahar, C.V.: · 2015
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Discovering the spatial extent of relative attributes
Xiao, F., Jae Lee, Y.: · 2015
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Highlight detection with pairwise deep ranking for first-person video summarization
Yao, T., Mei, T., Rui, Y.: · 2016
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