SBBD

Paper Registration

1

Select Book

2

Select Paper

3

Fill in paper information

4

Congratulations

Fill in your paper information

English Information

(*) To change the order drag the item to the new position.

Authors
# Name
1 João Pedro Ferreira(joaoferreira@dcc.ufmg.br)
2 Renato Martins(renato.martins@inria.fr)
3 Erickson Nascimento(erickson@dcc.ufmg.br)

(*) To change the order drag the item to the new position.

Reference
# Reference
1 Aytar, Y., Vondrick, C., and Torralba, A. (2016). Soundnet: Learning sound representations from unlabeled video. In Advances in neural information processing systems.
2 Cao, Z., Hidalgo Martinez, G., Simon, T., Wei, S., and Sheikh, Y. A. (2019). Openpose: Realtime multi-person 2d pose estimation using part affinity fields. IEEE Transactions on Pattern Analysis and Machine Intelligence.
3 Ferreira, J. P., Coutinho, T. M., Gomes, T. L., Neto, J. F., Azevedo, R., Martins, R., and Nascimento, E. R. (2020). Learning to dance: A graph convolutional adversarial network to generate realistic dance motions from audio. Computers & Graphics.
4 Gomes, T. L., Martins, R., Ferreira, J., Azevedo, R., Torres, G., and Nascimento, E. R. (2021). A shape-aware retargeting approach to transfer human motion and appearance in monocular videos. International Journal of Computer Vision.
5 Gomes, T. L., Martins, R., Ferreira, J., and Nascimento, E. R. (2020). Do as I do: transferring human motion and appearance between monocular videos with spatial and temporal constraints. In IEEE Conference on Applications of Computer Vision (WACV).
6 Huang, R., Hu, H., Wu, W., Sawada, K., and Zhang, M. (2021). Dance revolution: Long sequence dance generation with music via curriculum learning. In ICLR 2021.
7 Kipf, T. N. and Welling, M. (2017). Semi-supervised classification with graph convolutional networks. In ICLR.
8 Lee, H.-Y., Yang, X., Liu, M.-Y., Wang, T.-C., Lu, Y.-D., Yang, M.-H., and Kautz, J. (2019). Dancing to music. In Advances in Neural Information Processing Systems.
9 Li, J., Yin, Y., Chu, H., Zhou, Y., Wang, T., Fidler, S., and Li, H. (2020). Learning to generate diverse dance motions with transformer. arXiv preprint arXiv:2008.08171.
10 Li, R., Yang, S., Ross, D. A., and Kanazawa, A. (2021). Learn to dance with aist++: Music conditioned 3d dance generation. In eprint arXiv: 2101.08779.
11 Wang, T.-C., Liu, M.-Y., Zhu, J.-Y., Liu, G., Tao, A., Kautz, J., and Catanzaro, B. (2018). Video-to-video synthesis. In Conference on Neural Information Processing Systems.
12 Yan, S., Xiong, Y., and Lin, D. (2018). Spatial temporal graph convolutional networks for skeleton-based action recognition. In AAAI Conference on Artificial Intelligence.