The Menpo Facial Landmark Localisation Challenge: A Step Towards the Solution

IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops

Volumn 2017-July, Issue , 2017, Pages 2116-2125

  Zafeiriou, Stefanos ^a   Trigeorgis, George ^a   Chrysos, Grigorios ^a   Deng, Jiankang ^a   Shen, Jie ^a  

^a IMPERIAL COLLEGE LONDON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION; DEEP LEARNING; LEARNING ALGORITHMS;

FACIAL IMAGES; FACIAL LANDMARK; LEARNING ARCHITECTURES;

PATTERN RECOGNITION;

EID: 85030223503     PISSN: 21607508     EISSN: 21607516     Source Type: Conference Proceeding    
DOI: 10.1109/CVPRW.2017.263     Document Type: Conference Paper

References (52)

1. J. Alabort-i Medina, E. Antonakos, J. Booth, P. Snape, and S. Zafeiriou. Menpo: A comprehensive platform for parametric image alignment and visual deformable models. In Proceedings of the 22nd ACM international conference on Multimedia, pages 679-682. ACM, 2014.
2. J. Alabort-i Medina and S. Zafeiriou. A unified framework for compositional fitting of active appearance models. International Journal of Computer Vision, pages 1-39, 2016.
3. E. Antonakos, J. Alabort-i-Medina, G. Tzimiropoulos, and S. Zafeiriou. Feature-based lucas-kanade and active appearance models. IEEE Transactions on Image Processing, 24 (9):2617-2632, September 2015.
4. E. Antonakos, P. Snape, G. Trigeorgis, and S. Zafeiriou. Adaptive cascaded regression. In Proceedings of the IEEE International Conference on Image Processing (ICIP), 2016.
5. A. Asthana, S. Zafeiriou, S. Cheng, and M. Pantic. Incremental face alignment in the wild. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 1859-1866, 2014.
6. P. N. Belhumeur, D. W. Jacobs, D. J. Kriegman, and N. Kumar. Localizing parts of faces using a consensus of exemplars. In IEEE Transactions on Pattern Analysis and Machine Intelligence, volume 35, pages 2930-2940, December 2013.
7. J. Booth, E. Antonakos, S. Ploumpis, G. Trigeorgis, Y. Panagakis, and S. Zafeiriou. 3D Face Morphable Models "In-the-Wild". In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, July 2017.
8. J. Booth, A. Roussos, S. Zafeiriou, A. Ponniah, and D. Dunaway. A 3d morphable model learnt from 10, 000 faces. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, June 2016.
9. A. Bulat and G. Tzimiropoulos. Two-stage convolutional part heatmap regression for the 1st 3d face alignment in the wild (3dfaw) challenge. In Proceedings of the European Conference on Computer Vision Workshop, pages 616-624. Springer, 2016.
10. X. Cao, Y. Wei, F. Wen, and J. Sun. Face alignment by explicit shape regression. International Journal of Computer Vision, 107 (2):177-190, 2014.
11. X. Chen, E. Zhou, J. Liu, and Y. Mo. Delving Deep into Coarse-to-fine Framework for Facial Landmark Localization. In Proceedings of the International Conference on Computer Vision & Pattern Recognition (CVPRW), Facesin-the-wild Workshop/Challenge, 2017.
12. G. G. Chrysos, E. Antonakos, P. Snape, A. Asthana, and S. Zafeiriou. A comprehensive performance evaluation of deformable face tracking "in-the-wild". CoRR, abs/1603. 06015, 2016.
13. J. S. Chung, A. Senior, O. Vinyals, and A. Zisserman. Lip reading sentences in the wild. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2017.
14. J. S. Chung and A. Zisserman. Lip reading in the wild. In Proceedings of the Asian Conference on Computer Vision, 2016.
15. D. Cristinacce and T. F. Cootes. Feature detection and tracking with constrained local models. In Proceedings of the British Machine Vision Conference.
16. J. Deng, Q. Liu, J. Yang, and D. Tao. M 3 csr: multi-view, multi-scale and multi-component cascade shape regression. Image and Vision Computing, 47:19-26, 2016.
17. J. Deng, G. Trigeorgis, and S. Zafeiriou. Coarse-to-fine deformable face modelling: A 2. 5d approach. arXiv preprint, 2017.
18. S. Eleftheriadis, O. Rudovic, M. P. Deisenroth, and M. Pantic. Gaussian process domain experts for model adaptation in facial behavior analysis. In Proceedings of the International Conference on Computer Vision and Pattern Recognition Workshops, 2016.
19. S. Eleftheriadis, O. Rudovic, and M. Pantic. Joint facial action unit detection and feature fusion: A multi-conditional learning approach. IEEE Transactions on Image Processing, 25 (12):5727-5742, 2016.
20. H. Fan and E. Zhou. Approaching human level facial landmark localization by deep learning. Image and Vision Computing, 47:27-35, 2016.
21. Z.-H. Feng, J. Kittler, M. Awais, P. Huber, and X. Wu. Face Detection, Bounding Box Aggregation and Pose Estimation for Robust Facial Landmark Localisation in the Wild. In Proceedings of the International Conference on Computer Vision & Pattern Recognition (CVPRW), Faces-in-the-wild Workshop/Challenge, 2017.
22. R. A. Güler, G. Trigeorgis, E. Antonakos, P. Snape, S. Zafeiriou, and I. Kokkinos. Densereg: Fully convolutional dense shape regression in-the-wild. Proceedings of the International Conference on Pattern Recognition and Computer Vision, 2016.
23. K. He, X. Zhang, S. Ren, and J. Sun. Deep residual learning for image recognition. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 770-778, 2016.
24. Z. He, J. Zhang, M. Kan, S. Shan, and X. Chen. Robust FECCNN: A High Accuracy Facial Landmark Detection System. In Proceedings of the International Conference on Computer Vision & Pattern Recognition (CVPRW), Faces-in-the-wild Workshop/Challenge, 2017.
25. L. A. Jeni, S. Tulyakov, L. Yin, N. Sebe, and J. F. Cohn. The first 3d face alignment in the wild (3dfaw) challenge. In Proceedings of the European Conference on Computer Vision, pages 511-520. Springer, 2016.
26. M. Köstinger, P. Wohlhart, P. M. Roth, and H. Bischof. Annotated facial landmarks in the wild: A large-scale, realworld database for facial landmark localization. In Proceedings of the International Conference on Computer Vision, pages 2144-2151. IEEE, 2011.
27. M. Kowalski, J. Naruniec, and T. Trzcinski. Deep Alignment Network: A convolutional neural network for robust face alignment. In Proceedings of the International Conference on Computer Vision & Pattern Recognition (CVPRW), Faces-in-the-wild Workshop/Challenge, 2017.
28. V. Le, J. Brandt, Z. Lin, L. Bourdev, and T. Huang. Interactive facial feature localization. Proceedings of the European Conference on Computer Vision, pages 679-692, 2012.
29. S. Milborrow and F. Nicolls. Active shape models with sift descriptors and mars. In Proceedings of the 2014 International Conference on Computer Vision Theory and Applications (VISAPP), volume 2, pages 380-387. IEEE, 2014.
30. H. Nam and B. Han. Learning multi-domain convolutional neural networks for visual tracking. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 4293-4302, 2016.
31. A. Newell, K. Yang, and J. Deng. Stacked hourglass networks for human pose estimation. In Proceedings of the European Conference on Computer Vision, pages 483-499. Springer, 2016.
32. S. Ren, X. Cao, Y. Wei, and J. Sun. Face alignment at 3000 fps via regressing local binary features. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 1685-1692, 2014.
33. C. Sagonas, E. Antonakos, G. Tzimiropoulos, S. Zafeiriou, and M. Pantic. 300 faces in-the-wild challenge: Database and results. Image and Vision Computing, 47:3-18, 2016.
34. C. Sagonas, G. Tzimiropoulos, S. Zafeiriou, and M. Pantic. 300 faces in-the-wild challenge: The first facial landmark localization challenge. In Proceedings of the IEEE International Conference on Computer Vision Workshops, pages 397-403, 2013.
35. J. M. Saragih, S. Lucey, and J. F. Cohn. Deformable model fitting by regularized landmark mean-shift. International Journal of Computer Vision, 91 (2):200-215, 2011.
36. X.-H. Shao, J. Xing, J. Lv, C. Xiao, P. Liu, Y. Feng, C. Cheng, and F. Si. Unconstrained Face Alignment without Face Detection. In Proceedings of the International Conference on Computer Vision & Pattern Recognition (CVPRW), Faces-in-the-wild Workshop/Challenge, 2017.
37. J. Shen, S. Zafeiriou, G. G. Chrysos, J. Kossaifi, G. Tzimiropoulos, and M. Pantic. The first facial landmark tracking in-the-wild challenge: Benchmark and results. In Proceedings of the IEEE International Conference on Computer Vision Workshop (ICCVW), pages 1003-1011. IEEE, 2015.
38. Z. Shu, E. Yumer, S. Hadap, K. Sunkavalli, E. Shechtman, and D. Samaras. Neural face editing with intrinsic image disentangling. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages-. IEEE, 2017.
39. K. Simonyan and A. Zisserman. Very deep convolutional networks for large-scale image recognition. CoRR, abs/1409. 1556, 2014.
40. B. M. Smith, J. Brandt, Z. Lin, and L. Zhang. Nonparametric context modeling of local appearance for pose-and expression-robust facial landmark localization. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 1741-1748, 2014.
41. Y. Taigman, M. Yang, M. Ranzato, and L. Wolf. Deepface: Closing the gap to human-level performance in face verifica-tion. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 1701-1708, 2014.
42. G. Trigeorgis, P. Snape, E. Antonakos, M. A. Nicolaou, and S. Zafeiriou. Mnemonic Descent Method: A recurrent process applied for end-to-end face alignment. In Proceedings of the International Conference on Computer Vision and Pattern Recognition, 2016.
43. W. Wu and S. Yang. Leveraging Intra and Inter-Dataset Variations for Robust Face Alignment. In Proceedings of the International Conference on Computer Vision & Pattern Recognition (CVPRW), Faces-in-the-wild Workshop/ Challenge, 2017.
44. S. Xiao, J. Li, Y. Chen, Z. Wang, J. Feng, Y. Shuicheng, and A. Kassim. 3D-assisted Coarse-to-fine Extreme-pose Facial Landmark Detection. In Proceedings of the International Conference on Computer Vision & Pattern Recognition (CVPRW), Faces-in-the-wild Workshop/Challenge, 2017.
45. X. Xiong and F. De la Torre. Supervised descent method and its applications to face alignment. In Proceedings of the IEEE conference on computer vision and pattern recognition, pages 532-539, 2013.
46. X. Xiong and F. De la Torre. Global supervised descent method. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 2664-2673, 2015.
47. J. Yang, Q. Liu, and K. Zhang. Stacked Hourglass Network for Robust Facial Landmark Localisation. In Proceedings of the International Conference on Computer Vision & Pattern Recognition (CVPRW), Faces-in-the-wild Workshop/ Challenge, 2017.
48. A. Zadeh, T. Baltrusaitis, and L.-P. Morency. Convolutional Experts Network for Facial Landmark Detection. In Proceedings of the International Conference on Computer Vision & Pattern Recognition (CVPRW), Faces-in-the-wild Workshop/Challenge, 2017.
49. S. Zafeiriou, A. Roussos, A. Ponniah, D. Dunaway, and J. Booth. Large scale 3d morphable models. International Journal of Computer Vision, 2017.
50. K. Zhang, Z. Zhang, Z. Li, and Y. Qiao. Joint face detection and alignment using multitask cascaded convolutional networks. IEEE Signal Processing Letters, 23 (10):1499-1503, 2016.
51. S. Zhu, C. Li, C. Change Loy, and X. Tang. Face alignment by coarse-to-fine shape searching. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 4998-5006, 2015.
52. X. Zhu and D. Ramanan. Face detection, pose estimation, and landmark localization in the wild. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 2879-2886. IEEE, 2012.