Deep laplacian pyramid networks for fast and accurate super-resolution

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

Volumn 2017-January, Issue , 2017, Pages 5835-5843

  Lai, Wei Sheng ^a   Huang, Jia Bin ^b   Ahuja, Narendra ^c   Yang, Ming Hsuan ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY   (United States)

^c UNIVERSITY OF ILLINOIS AT URBANA CHAMPAIGN   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION; CONVOLUTION; LAPLACE TRANSFORMS; NEURAL NETWORKS; OPTICAL RESOLVING POWER;

BICUBIC INTERPOLATION; CONVOLUTIONAL NEURAL NETWORK; HIGH QUALITY RECONSTRUCTION; HIGH RESOLUTION IMAGE; MULTI SCALE PREDICTION; PRE-PROCESSING STEP; QUALITATIVE EVALUATIONS; STATE-OF-THE-ART METHODS;

IMAGE RECONSTRUCTION;

EID: 85041899955     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2017.618     Document Type: Conference Paper

References (39)

1. P. Arbelaez, M. Maire, C. Fowlkes, and J. Malik. Contour detection and hierarchical image segmentation. TPAMI, 33(5):898-916, 2011. 4, 5
2. M. Bevilacqua, A. Roumy, C. Guillemot, and M. L. Alberi-Morel. Low-complexity single-image super-resolution based on nonnegative neighbor embedding. In BMVC, 2012. 2, 5
3. A. Bruhn, J. Weickert, and C. Schnörr. Lucas/Kanade meets Horn/Schunck: Combining local and global optic flow methods. IJCV, 61(3):211-231, 2005. 4
4. P. J. Burt and E. H. Adelson. The Laplacian pyramid as a compact image code. IEEE Transactions on Communications, 31(4):532-540, 1983. 3
5. H. Chang, D.-Y. Yeung, and Y. Xiong. Super-resolution through neighbor embedding. In CVPR, 2004. 2
6. E. L. Denton, S. Chintala, and R. Fergus. Deep generative image models using a laplacian pyramid of adversarial networks. In NIPS, 2015. 3
7. C. Dong, C. C. Loy, K. He, and X. Tang. Image super-resolution using deep convolutional networks. TPAMI, 38(2):295-307, 2015. 1, 2, 3, 5, 6, 7, 8
8. C. Dong, C. C. Loy, and X. Tang. Accelerating the super-resolution convolutional neural network. In ECCV, 2016. 1, 2, 3, 5, 6, 7, 8
9. G. Freedman and R. Fattal. Image and video upscaling from local self-examples. ACM TOG (Proc. of SIGGRAPH), 30(2):12, 2011. 2
10. W. T. Freeman, T. R. Jones, and E. C. Pasztor. Example-based super-resolution. IEEE, Computer Graphics and Applications, 22(2):56-65, 2002. 2
11. G. Ghiasi and C. C. Fowlkes. Laplacian pyramid reconstruction and refinement for semantic segmentation. In ECCV, 2016. 3
12. D. Glasner, S. Bagon, and M. Irani. Super-resolution from a single image. In ICCV, 2009. 2
13. K. He, X. Zhang, S. Ren, and J. Sun. Delving deep into rectifiers: Surpassing human-level performance on imagenet classification. In ICCV, 2015. 4
14. D. J. Heeger and J. R. Bergen. Pyramid-based texture analysis/synthesis. In SIGGRAPH, 1995. 3
15. J.-B. Huang, A. Singh, and N. Ahuja. Single image super-resolution from transformed self-exemplars. In CVPR, 2015. 2, 5, 6, 7, 8
16. J. Johnson, A. Alahi, and L. Fei-Fei. Perceptual losses for real-time style transfer and super-resolution. In ECCV, 2016. 3
17. J. Kim, J. K. Lee, and K. M. Lee. Accurate image super-resolution using very deep convolutional networks. In CVPR, 2016. 1, 2, 3, 4, 5, 6, 7, 8
18. J. Kim, J. K. Lee, and K. M. Lee. Deeply-recursive convolutional network for image super-resolution. In CVPR, 2016. 2, 3, 5, 6, 7, 8
19. K. I. Kim and Y. Kwon. Single-image super-resolution using sparse regression and natural image prior. TPAMI, 32(6):1127-1133, 2010. 2
20. C. Ledig, L. Theis, F. Huszar, J. Caballero, A. Cunningham, A. Acosta, A. Aitken, A. Tejani, J. Totz, Z. Wang, and W. Shi. Photo-realistic single image super-resolution using a generative adversarial network. In CVPR, 2017. 3
21. C. Lee, S. Xie, P. Gallagher, Z. Zhang, and Z. Tu. Deeply-supervised nets, 2015. In International Conference on Artificial Intelligence and Statistics, 2015. 4
22. R. Liao, X. Tao, R. Li, Z. Ma, and J. Jia. Video super-resolution via deep draft-ensemble learning. In ICCV, 2015. 8
23. Y. Matsui, K. Ito, Y. Aramaki, T. Yamasaki, and K. Aizawa. Sketch-based manga retrieval using manga109 dataset. Multimedia Tools and Applications, pages 1-28, 2016. 5
24. S. Paris, S. W. Hasinoff, and J. Kautz. Local laplacian filters: Edge-aware image processing with a laplacian pyramid. ACM TOG (Proc. of SIGGRAPH), 30(4):68, 2011. 3
25. P. O. Pinheiro, T.-Y. Lin, R. Collobert, and P. Dollár. Learning to refine object segments. In ECCV, 2016. 3
26. S. Schulter, C. Leistner, and H. Bischof. Fast and accurate image upscaling with super-resolution forests. In CVPR, 2015. 1, 2, 4, 5, 6, 7
27. H. R. Sheikh, A. C. Bovik, and G. De Veciana. An information fidelity criterion for image quality assessment using natural scene statistics. TIP, 14(12):2117-2128, 2005. 6
28. W. Shi, J. Caballero, F. Huszar, J. Totz, A. Aitken, R. Bishop, D. Rueckert, and Z. Wang. Real-time single image and video super-resolution using an efficient sub-pixel convolutional neural network. In CVPR, 2016. 1, 3
29. A. Singh and N. Ahuja. Super-resolution using sub-band self-similarity. In ACCV, 2014. 2
30. R. Timofte, V. De Smet, and L. Van Gool. A+: Adjusted anchored neighborhood regression for fast super-resolution. In ACCV, 2014. 1, 2, 5, 6, 7
31. A. Vedaldi and K. Lenc. MatConvNet: Convolutional neural networks for matlab. In ACM MM, 2015. 5
32. Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli. Image quality assessment: From error visibility to structural similarity. TIP, 13(4):600-612, 2004. 6
33. Z. Wang, D. Liu, J. Yang, W. Han, and T. Huang. Deep networks for image super-resolution with sparse prior. In ICCV, 2015. 1, 2, 3, 5, 6, 7
34. S. Xie and Z. Tu. Holistically-nested edge detection. In CVPR, 2015. 4
35. C.-Y. Yang, C. Ma, and M.-H. Yang. Single-image super-resolution: a benchmark. In ECCV. 2014. 6
36. C.-Y. Yang and M.-H. Yang. Fast direct super-resolution by simple functions. In ICCV, 2013. 1, 2
37. J. Yang, J. Wright, T. Huang, and Y. Ma. Image super-resolution as sparse representation of raw image patches. In CVPR, 2008. 1, 2
38. J. Yang, J. Wright, T. S. Huang, and Y. Ma. Image super-resolution via sparse representation. TIP, 19(11):2861-2873, 2010. 1, 2, 4
39. R. Zeyde, M. Elad, and M. Protter. On single image scale-up using sparse-representations. In Curves and Surfaces. 2010. 2, 5