Hallucinating very low-Resolution unaligned and noisy face images by transformative discriminative autoencoders

Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017

Volumn 2017-January, Issue , 2017, Pages 5367-5375

  Yu, Xin ^a   Porikli, Fatih ^a  

^a AUSTRALIAN NATIONAL UNIVERSITY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION; DECODING; LEARNING SYSTEMS;

AUTOENCODERS; DISCRIMINATIVE AUTOENCODER; ENCODER-DECODER; FACE HALLUCINATION; LARGE MARGINS; LOW RESOLUTION; LOW-RESOLUTION FACE IMAGES; STATE OF THE ART;

NETWORK CODING;

EID: 85044119060     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2017.570     Document Type: Conference Paper

References (30)

1. S. Baker and T. Kanade. Hallucinating faces. In Proceedings of 4th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2000, pages 83–88, 2000. 1
2. S. Baker and T. Kanade. Limits on super-resolution and how to break them. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(9):1167–1183, 2002. 1, 2
3. J. Bruna, P. Sprechmann, and Y. LeCun. Super-resolution with deep convolutional sufficient statistics. In ICLR, 2016. 2
4. K. Dabov, A. Foi, V. Katkovnik, and K. Egiazarian. Image denoising by sparse 3-d transform-domain collaborative filtering. IEEE Transactions on image processing, 16(8):2080–2095, 2007. 1, 6
5. E. Denton, S. Chintala, A. Szlam, and R. Fergus. Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks. In Advances In Neural Information Processing Systems (NIPS), pages 1486–1494, 2015. 5
6. C. Dong, C. C. Loy, and K. He. Image Super-Resolution Using Deep Convolutional Networks. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(2):295–307, 2016. 2, 6, 7, 8
7. I. Goodfellow, J. Pouget-Abadie, and M. Mirza. Generative Adversarial Networks. In Advances in Neural Information Processing Systems (NIPS), pages 2672-2680, 2014. 5
8. P. H. Hennings-Yeomans, S. Baker, and B. V. Kumar. Simultaneous super-resolution and feature extraction for recognition of low-resolution faces. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), pages 1–8. IEEE, 2008. 1
9. G. Hinton. Neural Networks for Machine Learning Lecture 6a: Overview of mini-batch gradient descent Reminder: The error surface for a linear neuron. 5
10. M. Jaderberg, K. Simonyan, A. Zisserman, et al. Spatial transformer networks. In Advances in Neural Information Processing Systems, pages 2017–2025, 2015. 1, 2, 3, 4
11. J. Kim, J. K. Lee, and K. M. Lee. Accurate Image Super-Resolution Using Very Deep Convolutional Networks. arXiv:1511.04587, 2015. 2
12. S. Kolouri and G. K. Rohde. Transport-based single frame super resolution of very low resolution face images. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), 2015. 1, 2
13. Y. Li, C. Cai, G. Qiu, and K. M. Lam. Face hallucination based on sparse local-pixel structure. Pattern Recognition, 47(3):1261–1270, 2014. 1, 2
14. C. Liu, H. Shum, and C. Zhang. A two-step approach to hallucinating faces: global parametric model and local nonparametric model. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), volume 1, pages 192–198, 2001. 1
15. C. Liu, H. Y. Shum, and W. T. Freeman. Face hallucination: Theory and practice. International Journal of Computer Vision, 75(1):115–134, 2007. 1, 2
16. C. Liu, J. Yuen, and A. Torralba. Sift flow: Dense correspondence across scenes and its applications. IEEE transactions on pattern analysis and machine intelligence, 33(5):978–994, 2011. 2
17. A. Radford, L. Metz, and S. Chintala. Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks. arXiv:1511.06434, pages 1–15, 2015. 5
18. M. F. Tappen and C. Liu. A Bayesian Approach to Alignment-Based Image Hallucination. In Proceedings of European Conference on Computer Vision (ECCV), volume 7578, pages 236–249, 2012. 1, 2
19. N. Wang, D. Tao, X. Gao, X. Li, and J. Li. A comprehensive survey to face hallucination. International Journal of Computer Vision, 106(1):9–30, 2014. 1, 2
20. X. Wang and X. Tang. Hallucinating face by eigen transformation. IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews, 35(3):425–434, 2005. 1, 2
21. Z. Wang, Y. Yang, Z. Wang, S. Chang, W. Han, J. Yang, and T. Huang. Self-tuned deep super resolution. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pages 1–8, 2015. 2
22. C. Q. Xiang Ma, Junping Zhang. Hallucinating face by position-patch. Pattern Recognition, 43(6):2224–2236, 2010. 1, 2, 6, 7, 8
23. C. Y. Yang, S. Liu, and M. H. Yang. Structured face hallucination. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), pages 1099–1106, 2013. 1, 2
24. J. Yang, J. Wright, T. S. Huang, and Y. Ma. Image super-resolution via sparse representation. IEEE transactions on image processing, 19(11):2861–73, 2010. 1, 2
25. X. Yu and F. Porikli. Ultra-resolving face images by discriminative generative networks. In Proceedings of European Conference on Computer Vision (ECCV), pages 318–333, 2016. 1, 2, 3, 4, 5, 6, 7, 8
26. M. D. Zeiler and R. Fergus. Visualizing and understanding convolutional networks. In European Conference on Computer Vision, pages 818–833, 2014. 3
27. M. D. Zeiler, D. Krishnan, G. W. Taylor, and R. Fergus. De-convolutional networks. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), pages 2528–2535, 2010. 3
28. E. Zhou and H. Fan. Learning Face Hallucination in the Wild. In Twenty-Ninth AAAI Conference on Artificial Intelligence, pages 3871–3877, 2015. 1, 2
29. S. Zhu, S. Liu, C. C. Loy, and X. Tang. Deep cascaded bi-network for face hallucination. In Proceedings of European Conference on Computer Vision (ECCV), pages 614–630, 2016. 1, 2, 3, 5, 7, 8
30. X. W. Ziwei Liu, Ping Luo and X. Tang. Deep learning face attributes in the wild. In Proceedings of International Conference on Computer Vision (ICCV), 2015. 6