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Automatic photo cropping is an important tool for improving visual quality of digital photos without resorting to tedious manual selection.
An efficient boosting algorithm for combining preferences
Y. Freund, R. Iyer, R. E. Schapire, and Y. Singer · 2003
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Automatic thumbnail cropping and its effectiveness
B. Suh, H. Ling, B. B. Bederson, and D. W. Jacobs · 2003
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Learning to rank using gradient descent
C. Burges, T. Shaked, E. Renshaw, A. Lazier, M. Deeds, N. Hamilton, and G. Hullender · 2005
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Auto cropping for digital photographs
M. Zhang, L. Zhang, Y. Sun, L. Feng, and W. Ma · 2005
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Studying aesthetics in photographic images using a computational approach
R. Datta, D. Joshi, J. Li, and J. Z. Wang · 2006
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Training linear SVMs in linear time
T. Joachims · 2006
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The design of high-level features for photo quality assessment
Y. Ke, X. Tang, and F. Jing · 2006
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Gaze-based interaction for semi-automatic photo cropping
A. Santella, M. Agrawala, D. DeCarlo, D. Salesin, and M. Cohen · 2006
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A note on Platt’s probabilistic outputs for support vector machines
H.-T. Lin, C.-J. Lin, and R. C. Weng · 2007
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Attention based auto image cropping
F. Stentiford · 2007
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Finding good composition in panoramic scenes
Y.-Y. Chang and H.-T. Chen · 2009
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A framework for visual saliency detection with applications to image thumbnailing
L. Marchesotti, C. Cifarelli, and G. Csurka · 2009
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Sensation-based photo cropping
M. Nishiyama, T. Okabe, Y. Sato, and I. Sato · 2009
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A framework for photo-quality assessment and enhancement based on visual aesthetics
S. Bhattacharya, R. Sukthankar, and M. Shah · 2010
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Learning to photograph
B. Cheng, B. Ni, S. Yan, and Q. Tian · 2010
Cited alongside, same era.
Optimizing photo composition
L. Liu, R. Chen, L. Wolf, and D. Cohen-Or · 2010
Cited alongside, same era.
Adapting boosting for information retrieval measures
Q. Wu, C. J. Burges, K. M. Svore, and J. Gao · 2010
Cited alongside, same era.
High level describable attributes for predicting aesthetics and interestingness
S. Dhar, V. Ordonez, and T. L. Berg · 2011
Cited alongside, same era.
Content-based photo quality assessment
W. Luo, X. Wang, and X. Tang · 2011
Cited alongside, same era.
Assessing the aesthetic quality of photographs using generic image descriptors
L. Marchesotti, F. Perronnin, D. Larlus, and G. Csurka · 2011
Cited alongside, same era.
Probabilistic graphlet transfer for photo cropping
L. Zhang, M. Song, Q. Zhao, X. Liu, J. Bu, and C. Chen · 2013
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Automatic image cropping using visual composition, boundary simplicity and content preservation models
C. Fang, Z. Lin, R. Mech, and X. Shen · 2014
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What makes a photograph memorable?
P. Isola, J. Xiao, D. Parikh, A. Torralba, and A. Oliva · 2014
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Caffe: Convolutional architecture for fast feature embedding
Y. Jia, E. Shelhamer, J. Donahue, S. Karayev, J. Long, R. Girshick, S. Guadarrama, and T. Darrell · 2014
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Convolutional neural networks for no-reference image quality assessment
L. Kang, P. Ye, Y. Li, and D. Doermann · 2014
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Recognizing image style
S. Karayev, M. Trentacoste, H. Han, A. Agarwala, T. Darrell, A. Hertzmann, and H. Winnemoeller · 2014
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Unbiased look at dataset bias
A. Torralba and A. A. Efros · 2011
Cited alongside, same era.
ImageNet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
Cited alongside, same era.
AVA: A large-scale database for aesthetic visual analysis
N. Murray, L. Marchesotti, and F. Perronnin · 2012
Cited alongside, same era.
Preference-aware view recommendation system for scenic photos based on bag-of-aesthetics-preserving features
H.-H. Su, T.-W. Chen, C.-C. Kao, W. H. Hsu, and S.-Y. Chien · 2012
Cited alongside, same era.
Oscar: On-site composition and aesthetics feedback through exemplars for photographers
L. Yao, P. Suryanarayan, M. Qiao, J. Z. Wang, and J. Li · 2012
Cited alongside, same era.
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 · 2013
Cited alongside, same era.
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Microsoft COCO: Common objects in context
T.-Y. Lin, M. Maire, S. Belongie, J. Hays, P. Perona, D. Ramanan, P. Dollár, and C. L. Zitnick · 2014
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RAPID: Rating pictorial aesthetics using deep learning
X. Lu, Z. Lin, H. Jin, J. Yang, and J. Z. Wang · 2014
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Large-scale optimization of hierarchical features for saliency prediction in natural images
E. Vig, M. Dorr, and D. Cox · 2014
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Learning fine-grained image similarity with deep ranking
J. Wang, Y. Song, T. Leung, C. Rosenberg, J. Wang, J. Philbin, B. Chen, and Y. Wu · 2014
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Actively learning human gaze shifting paths for semantics-aware photo cropping
L. Zhang, Y. Gao, R. Ji, Y. Xia, Q. Dai, and X. Li · 2014
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Deep multi-patch aggregation network for image style, aesthetics, and quality estimation
X. Lu, Z. Lin, X. Shen, R. Mech, and J. Z. Wang · 2015
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Automatic image cropping : A computational complexity study
J. Chen, G. Bai, S. Liang, and Z. Li · 2016
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