Beat Based Realistic Dance Video Generation using Deep Learning

CCDS Authors

M Ashraful Amin, PhD

Founder DirectorDirector, Artificial Intelligence & Machine Learning WingDirector, Human-Computer Interaction WingDirector, Data Science Wing

References

1. 1.Zhou Wang, Alan C. Bovik, Hamid R. Sheikh, Eero P. Simoncelli. (2004). Image quality assessment: from error visibility to structural similarity. IEEE Transactions on Image Processing, 13(4), 600–612[10.1109/tip.2003.819861]
2. 2.Richard Zhang, Phillip Isola, Alexei A. Efros, Eli Shechtman, Oliver Wang. (2018). The Unreasonable Effectiveness of Deep Features as a Perceptual Metric. , 586–595[10.1109/cvpr.2018.00068]
3. 3.Justin Johnson, Alexandre Alahi, Li Fei-Fei. (2016). Perceptual Losses for Real-Time Style Transfer and Super-Resolution. Lecture notes in computer science, 694–711[10.1007/978-3-319-46475-6_43]
4. 4.Zhe Cao, Tomas Simon, Shih-En Wei, Yaser Sheikh. (2017). Realtime Multi-person 2D Pose Estimation Using Part Affinity Fields. , 1302–1310[10.1109/cvpr.2017.143]
5. 5.Brian McFee, Colin Raffel, Dawen Liang, Daniel P. W. Ellis, Matt McVicar, Eric Battenberg, Oriol Nieto. (2015). librosa: Audio and Music Signal Analysis in Python. Proceedings of the Python in Science Conferences, 18–24[10.25080/majora-7b98e3ed-003]
6. 6.Quan Huynh‐Thu, M. Ghanbari. (2008). Scope of validity of PSNR in image/video quality assessment. Electronics Letters, 44(13), 800–801[10.1049/el:20080522]
7. 7.Caroline Chan, Shiry Ginosar, Tinghui Zhou, Alexei A. Efros. (2019). Everybody Dance Now. , 5932–5941[10.1109/iccv.2019.00603]
8. 8.Daniel P. W. Ellis. (2007). Beat Tracking by Dynamic Programming. Journal of New Music Research, 36(1), 51–60[10.1080/09298210701653344]
9. 9.Masataka Goto. (2006). A chorus section detection method for musical audio signals and its application to a music listening station. IEEE Transactions on Audio Speech and Language Processing, 14(5), 1783–1794[10.1109/tsa.2005.863204]
10. 10.Taoran Tang, Jia Jia, Hanyang Mao. (2018). Dance with Melody. , 1598–1606[10.1145/3240508.3240526]
11. 11.Ferda Ofli, Engin Erzin, Y. Yemez, A. Murat Tekalp. (2011). Learn2Dance: Learning Statistical Music-to-Dance Mappings for Choreography Synthesis. IEEE Transactions on Multimedia, 14(3), 747–759[10.1109/tmm.2011.2181492]
12. 12.Nelson Yalta, Shinji Watanabe, Kazuhiro Nakadai, Tetsuya Ogata. (2019). Weakly-Supervised Deep Recurrent Neural Networks for Basic Dance Step Generation. , 1–8[10.1109/ijcnn.2019.8851872]
13. 13.Marwa A. Nasr, Mohammed Alrahmawy, A. S. Tolba. (2016). Multi-scale structural similarity index for motion detection. Journal of King Saud University - Computer and Information Sciences, 29(3), 399–409[10.1016/j.jksuci.2016.02.004]
14. 14.Takaaki Shiratori, Atsushi Nakazawa, Katsushi Ikeuchi. (2006). Synthesizing dance performance using musical and motion features. , 3654–3659[10.1109/robot.2006.1642260]
15. 15.Yi Wang, Zhiqiang Liu, Lizhu Zhou. (2005). Learning hierarchical non-parametric hidden Markov model of human motion. , 3315–3320 Vol. 6[10.1109/icmlc.2005.1527515]
16. 16.Richard Zhang, Phillip Isola, Alexei A. Efros, Eli Shechtman, Oliver Wang. (2018). The Unreasonable Effectiveness of Deep Features as a Perceptual Metric. arXiv (Cornell University)[10.48550/arxiv.1801.03924]
17. 17.Luka Crnkovic-Friis, Louise Crnkovic-Friis. (2016). Generative Choreography using Deep Learning. arXiv (Cornell University), 272–277[10.48550/arxiv.1605.06921]
18. 18.Juheon Lee, Seohyun Kim, Kyogu Lee. (2018). Listen to Dance: Music-driven choreography generation using Autoregressive Encoder-Decoder Network. arXiv (Cornell University)[10.48550/arxiv.1811.00818]