AVA: A large-scale database for aesthetic visual analysis

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn , Issue , 2012, Pages 2408-2415

  Murray, Naila ^a   Marchesotti, Luca ^b   Perronnin, Florent ^b  

^a UNIVERSITAT AUTÒNOMA DE BARCELONA   (Spain)

^b XEROX RESEARCH CENTRE EUROPE   (France)

Author keywords

[No Author keywords available]

Indexed keywords

AESTHETIC PREFERENCE; COMPUTATIONAL MODEL; LARGE-SCALE DATABASE; SEMANTIC LABELS; VISUAL ANALYSIS; VISUAL CONTENT;

COMPUTER VISION; SEMANTICS;

DATABASE SYSTEMS;

EID: 84866653001     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2012.6247954     Document Type: Conference Paper

References (21)

1. L. Bottou. Sgd. http://leon.bottou.org/projects/sgd. 6
2. D. Cramer and D. Howitt. The SAGE dictionary of statistics. SAGE, 1st edition, 2004. p. 21 (entry "ceiling effect"), p. 67 (entry "floor effect"). 4
3. R. Datta, D. Joshi, J. Li, and J. Z. Wang. Studying aesthetics in photographic images using a computational approach. In ECCV, pages 7-13, 2006. 1, 2
4. R. Datta, J. Li, and J. Z. Wang. Learning the consensus on visual quality for next-generation image management. In ACM-MM, 2007. 6
5. J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei. ImageNet: A Large-Scale Hierarchical Image Database. In CVPR09, 2009. 1
6. S. Dhar, V. Ordonez, and T. Berg. High level describable attributes for predicting aesthetics and interestingness. In CVPR, pages 1657-1664. IEEE, 2011. 1, 6, 7
7. M. Everingham, L. Van Gool, C. K. I. Williams, J. Winn, and A. Zisserman. The pascal visual object classes (voc) challenge. IJCV, 2010. 1
8. G. Griffin, A. Holub, and P. Perona. Caltech-256 object category dataset. Technical report, California Institute of Technology, 2007. 1
9. T. D. Henning Muller, Paul Clough and B. Caput. Experimental evaluation in visual information retrieval. the information retrieval series. Springer, 2010. 3
10. D. Joshi, R. Datta, E. Fedorovskaya, Q. Luong, J. Wang, J. Li, and J. Luo. Aesthetics and emotions in images. Signal Processing Magazine, IEEE, 28(5):94-115, 2011. 6
11. Y. Ke, X. Tang, and F. Jing. The design of high-level features for photo quality assessment. In CVPR, 2006. 1, 3, 6
12. Kodak. How to take good pictures : a photo guide. Random House Inc, 1982. 2
13. R. F. L. Fei-Fei and P. Perona. Learning generative visual models from few training examples: an incremental bayesian approach tested on 101 object categories. In CVPR, 2004. 1
14. D. Lowe. Distinctive image features from scale-invariant keypoints. IJCV, 60(2), 2004. 6
15. W. Luo, X.Wang, and X. Tang. Content-based photo quality assessment. In ICCV, 2011. 1, 3, 6, 7
16. Y. Luo and X. Tang. Photo and video quality evaluation: Focusing on the subject. In ECCV, 2008. 1, 6
17. L. Marchesotti, F. Perronnin, D. Larlus, and G. Csurka. Assessing the aesthetic quality of photographs using generic image descriptors. In ICCV, 2011. 1, 3, 6
18. F. Perronnin and C. Dance. Fisher kernels on visual vocabularies for image categorization. In CVPR, 2007. 6
19. F. Perronnin, J. Sánchez, and T. Mensink. Improving the Fisher kernel for large-scale image classification. In ECCV, 2010. 6
20. J. Russell. A circumplex model of affect. Journal of personality and social psychology, 39(6):1161, 1980. 5
21. O. Wu, W. Hu, and J. Gao. Learning to predict the perceived visual quality of photos. In ICCV, 2011. 3, 6