1 |
Fan, Haoqiang, Hao Su, and Leonidas J. Guibas. "A point set generation network for 3d object reconstruction from a single image," Proceedings of the IEEE conference on computer vision and pattern recognition, 2016. DOI: 10.48550/arXiv.1612.00603
DOI
|
2 |
Choy, C. B., Xu, D., Gwak, J., Chen, K., & Savarese, S.. "3d-r2n2: A unified approach for single and multi-view 3d object reconstruction," In European conference on computer vision, pp. 628-644. 2016. DOI: 10.48550/arXiv.1604.00449
DOI
|
3 |
KINGMA, Diederik P.; WELLING, Max. "Autoencoding variational bayes," International Conference on Learning Representations (ICLR), 2014. DOI: 10.48550/arXiv.1312.6114
DOI
|
4 |
Higgins, I., Matthey, L., Pal, A., Burgess, C., Glorot, X., Botvinick, M., Lerchner, A. "beta-vae: Learning basic visual concepts with a constrained variational framework." 2016.
|
5 |
Mandikal, P., Navaneet, K. L., Agarwal, M., Babu, R. V. "3D-LMNet: Latent embedding matching for accurate and diverse 3D point cloud reconstruction from a single image," Proceedings of the British Machine Vision Conference(BMVC), 2018. DOI:10.48550/arXiv.1807.07796
DOI
|
6 |
Li, B., Zhang, Y., Zhao, B., & Shao, H. "3D-ReConstnet: a single-view 3d-object point cloud reconstruction network," IEEE Access 8 pp.83782-83790. 2020. DOI: 10.1109/ACCESS.2020.2992554
DOI
|
7 |
Chang, A. X., Funkhouser, T., Guibas, L., Hanrahan, P., Huang, Q., Li, Z., ... & Yu, F.. "Shapenet: An information-rich 3d model repository," 2015. DOI: 10.48550/arXiv.1512.03012
DOI
|
8 |
He, K., Zhang, X., Ren, S., & Sun, J. (2016). "Deep residual learning for image recognition," In Proceedings of the IEEE conference on computer vision and pattern recognition, pp.770-778. DOI: 10.48550/arXiv.1512.03385
DOI
|