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In this work, we propose a novel approach for generating videos of the six basic facial expressions given a neutral face image.
H. Karcher, “Riemannian center of mass and mollifier smoothing,” Communications on Pure and Applied Mathematics , vol. 30, pp. 509–541, 1977
1977
Earlier work this paper cites.
S. Hochreiter and J. Schmidhuber, “Long short-term memory,” Neural computation , vol. 9, no. 8, pp. 1735–1780, 1997
1997
Earlier work this paper cites.
T. F. Cox and M. A. Cox, Multidimensional scaling . Chapman and hall/CRC, 2000
2000
Earlier work this paper cites.
I. Cohen, N. Sebe, A. Garg, L. S. Chen, and T. S. Huang, “Facial expression recognition from video sequences: temporal and static modeling,” Computer Vision and Image Understanding , vol. 91, no. 1, pp. 160 – 187, 2003, special Issue on Face Recognition. [Online]. Available: http://www.sciencedirect.com/science/article/pii/S107731420300081X
2003
Earlier work this paper cites.
Z. Wang, A. C. Bovik, H. R. Sheikh, E. P. Simoncelli et al. , “Image quality assessment: from error visibility to structural similarity,” IEEE Trans. on Image Processing , vol. 13, no. 4, pp. 600–612, 2004
2004
Earlier work this paper cites.
M. Pantic and I. Patras, “Dynamics of facial expression: recognition of facial actions and their temporal segments from face profile image sequences,” IEEE Trans. on Systems, Man, and Cybernetics, Part B (Cybernetics) , vol. 36, no. 2, pp. 433–449, April 2006
2006
Earlier work this paper cites.
N. Aifanti, C. Papachristou, and A. Delopoulos, “The mug facial expression database,” in Int. Workshop on Image Analysis for Multimedia Interactive Services (WIAMIS) . IEEE, 2010, pp. 1–4
2010
Earlier work this paper cites.
P. Lucey, J. F. Cohn, T. Kanade, J. Saragih, Z. Ambadar, and I. Matthews, “The extended cohn-kanade dataset (ck+): A complete dataset for action unit and emotion-specified expression,” in IEEE Conf. on Computer Vision and Pattern Recognition Workshops (CVPRW) , 2010, pp. 94–101
2010
Earlier work this paper cites.
A. Srivastava, E. Klassen, S. Joshi, and I. Jermyn, “Shape analysis of elastic curves in euclidean spaces,” IEEE Trans. pn Pattern Analysis and Machine Intelligence , vol. 33, no. 7, pp. 1415–1428, 2011
2011
Earlier work this paper cites.
G. Zhao, X. Huang, M. Taini, S. Z. Li, and M. PietikäInen, “Facial expression recognition from near-infrared videos,” Image and Vision Computing , vol. 29, no. 9, pp. 607–619, 2011
2011
Earlier work this paper cites.
Z. Zhou, G. Zhao, and M. Pietikäinen, “Towards a practical lipreading system,” in IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) , 2011, pp. 137–144
2011
Earlier work this paper cites.
H. Drira, B. Ben Amor, A. Srivastava, M. Daoudi, and R. Slama, “3D face recognition under expressions, occlusions, and pose variations,” IEEE Trans. Pattern Analysis and Machine Intelligence , vol. 35, no. 9, pp. 2270–2283, 2013
2013
Earlier work this paper cites.
I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio, “Generative adversarial nets,” in Advances in Neural Information Processing Systems 27 , Z. Ghahramani, M. Welling, C. Cortes, N. D. Lawrence, and K. Q. Weinberger, Eds. Curran Associates, Inc., 2014, pp. 2672–2680. [Online]. Available: http://papers.nips.cc/paper/5423-generative-adversarial-nets.pdf
2014
Earlier work this paper cites.
2014
Earlier work this paper cites.
M. Devanne, H. Wannous, S. Berretti, P. Pala, M. Daoudi, and A. Del Bimbo, “3-D human action recognition by shape analysis of motion trajectories on Riemannian manifold,” IEEE Trans. Cybernetics , vol. 45, no. 7, pp. 1340–1352, 2015. [Online]. Available: https://doi.org/10.1109/TCYB.2014.2350774
2014
Earlier work this paper cites.
2014
Earlier work this paper cites.
2015
Earlier work this paper cites.
O. Ronneberger, P. Fischer, and T. Brox, “U-net: Convolutional networks for biomedical image segmentation,” in Int. Conf. on Medical image computing and computer-assisted intervention . Springer, 2015, pp. 234–241
2015
Earlier work this paper cites.
J. Long, E. Shelhamer, and T. Darrell, “Fully convolutional networks for semantic segmentation,” in IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) , 2015, pp. 3431–3440
2015
Earlier work this paper cites.
J. Oh, X. Guo, H. Lee, R. L. Lewis, and S. Singh, “Action-conditional video prediction using deep networks in atari games,” in Advances in Neural Information Processing Systems (NIPS) , 2015, pp. 2863–2871
2015
Earlier work this paper cites.
H. Jung, S. Lee, J. Yim, S. Park, and J. Kim, “Joint fine-tuning in deep neural networks for facial expression recognition,” in IEEE Int. Conf. on Computer Vision (ICCV) , 2015, pp. 2983–2991
2015
Earlier work this paper cites.
O. M. Parkhi, A. Vedaldi, and A. Zisserman, “Deep face recognition,” in British Machine Vision Conf. (BMVC) . BMVA Press, 2015, pp. 41.1–41.12
2015
Cited alongside, same era.
Y. Zhou and T. L. Berg, “Learning temporal transformations from time-lapse videos,” in European Conf. on Computer Vision (ECCV) . Springer, 2016, pp. 262–277
2016
Cited alongside, same era.
C. Vondrick, H. Pirsiavash, and A. Torralba, “Generating videos with scene dynamics,” in Advances in Neural Information Processing Systems (NIPS) , D. D. Lee, M. Sugiyama, U. V. Luxburg, I. Guyon, and R. Garnett, Eds., 2016, pp. 613–621
2016
Cited alongside, same era.
M. Abadi, P. Barham, J. Chen, Z. Chen, A. Davis, J. Dean, M. Devin, S. Ghemawat, G. Irving, M. Isard et al. , “Tensorflow: A system for large-scale machine learning,” in Symposium on Operating Systems Design and Implementation ( { \{ OSDI } \} 16) , 2016, pp. 265–283
2016
Cited alongside, same era.
O. Wiles, A. Sophia Koepke, and A. Zisserman, “X2face: A network for controlling face generation using images, audio, and pose codes,” in European Conf. on Computer Vision (ECCV) , 2018, pp. 670–686
2018
Later among the works it cites.
F. Zhang, T. Zhang, Q. Mao, and C. Xu, “Joint pose and expression modeling for facial expression recognition,” in IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) , June 2018, pp. 3359–3368
2018
Later among the works it cites.
Y.-H. Lai and S.-H. Lai, “Emotion-preserving representation learning via generative adversarial network for multi-view facial expression recognition,” in IEEE Int. Conf. on Automatic Face & Gesture Recognition (FG) . IEEE, 2018, pp. 263–270
2018
Later among the works it cites.
A. Pumarola, A. Agudo, A. M. Martinez, A. Sanfeliu, and F. Moreno-Noguer, “Ganimation: Anatomically-aware facial animation from a single image,” in European Conf. on Computer Vision (ECCV) , 2018, pp. 818–833
2018
Later among the works it cites.
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B. Amos, B. Ludwiczuk, M. Satyanarayanan et al. , “Openface: A general-purpose face recognition library with mobile applications,” CMU School of Computer Science , vol. 6, 2016
2016
Cited alongside, same era.
2017
Cited alongside, same era.
P. Isola, J.-Y. Zhu, T. Zhou, and A. A. Efros, “Image-to-image translation with conditional adversarial networks,” CVPR , 2017
2017
Cited alongside, same era.
J.-Y. Zhu, T. Park, P. Isola, and A. A. Efros, “Unpaired image-to-image translation using cycle-consistent adversarial networks,” in IEEE Int. Conf. on Computer Vision (ICCV) , 2017, pp. 2223–2232
2017
Cited alongside, same era.
C. Ledig, L. Theis, F. Huszár, J. Caballero, A. Cunningham, A. Acosta, A. Aitken, A. Tejani, J. Totz, Z. Wang et al. , “Photo-realistic single image super-resolution using a generative adversarial network,” in IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) , 2017, pp. 4681–4690
2017
Cited alongside, same era.
Y. Zhou and B. E. Shi, “Photorealistic facial expression synthesis by the conditional difference adversarial autoencoder,” in Int. Conf. on Affective Computing and Intelligent Interaction (ACII) . IEEE, 2017, pp. 370–376
2017
Cited alongside, same era.
Z. Zhang, Y. Song, and H. Qi, “Age progression/regression by conditional adversarial autoencoder,” in IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) , 2017, pp. 5810–5818
2017
Cited alongside, same era.
X. Yin, X. Yu, K. Sohn, X. Liu, and M. Chandraker, “Towards large-pose face frontalization in the wild,” in IEEE Int. Conf. on Computer Vision (ICCV) , 2017, pp. 3990–3999
2017
Cited alongside, same era.
2018
Later among the works it cites.
2018
Later among the works it cites.
H. Kim, P. Garrido, A. Tewari, W. Xu, J. Thies, M. Nießner, P. Pérez, C. Richardt, M. Zollhöfer, and C. Theobalt, “Deep video portraits,” ACM Trans. on Graphics (TOG) , vol. 37, no. 4, pp. 1–14, 2018
2018
Later among the works it cites.
2018
Later among the works it cites.
S. Tulyakov, M. Liu, X. Yang, and J. Kautz, “Mocogan: Decomposing motion and content for video generation,” in IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) , 2018, pp. 1526–1535
2018
Later among the works it cites.
W. Wang, X. Alameda-Pineda, D. Xu, P. Fua, E. Ricci, and N. Sebe, “Every smile is unique: Landmark-guided diverse smile generation,” in IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) , 2018, pp. 7083–7092
2018
Later among the works it cites.
A. Kacem, M. Daoudi, B. B. Amor, S. Berretti, and J. C. Alvarez-Paiva, “A novel geometric framework on gram matrix trajectories for human behavior understanding,” IEEE Trans. on Pattern Analysis and Machine Intelligence , 2018
2018
Later among the works it cites.
L. Zhao, X. Peng, Y. Tian, M. Kapadia, and D. Metaxas, “Learning to forecast and refine residual motion for image-to-video generation,” in European Conf. on Computer Vision (ECCV) , 2018, pp. 387–403
2018
Later among the works it cites.
T. Baltrusaitis, A. Zadeh, Y. C. Lim, and L.-P. Morency, “Openface 2.0: Facial behavior analysis toolkit,” in IEEE Int. Conf. on Automatic Face & Gesture Recognition (FG) . IEEE, 2018, pp. 59–66
2018
Later among the works it cites.
——, “Deep covariance descriptors for facial expression recognition,” in British Machine Vision Conf. (BMVC) , Sept. 2018
2018
Later among the works it cites.
Z. Huang, J. Wu, and L. V. Gool, “Manifold-valued image generation with wasserstein adversarial networks,” in AAAI Conf. on Artificial Intelligence , 2019
2019
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2019
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2019
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K. Vougioukas, S. Petridis, and M. Pantic, “Realistic speech-driven facial animation with gans,” Int. Journal of Computer Vision , pp. 1–16, 2019
2019
Closest in time.
N. Otberdout, A. Kacem, M. Daoudi, L. Ballihi, and S. Berretti, “Automatic analysis of facial expressions based on deep covariance trajectories,” IEEE Trans. on Neural Networks and Learning Systems , 2019
2019
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D. Kollias, S. Cheng, E. Ververas, I. Kotsia, and S. Zafeiriou, “Deep neural network augmentation: Generating faces for affect analysis,” Int. Journal of Computer Vision , pp. 1–30, 2020
2020
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