1. Antipov, G., Baccouche, M., Dugelay, J.L.: Face aging with conditional generative adversarial networks (2017). arXiv preprint
arXiv:1702.01983
2. Bao, J., Chen, D., Wen, F., Li, H., Hua, G.: CVAE-GAN: fine-grained image generation through asymmetric training (2017). arXiv preprint
arXiv:1703.10155
3. Chang, A., Funkhouser, T., Guibas, L., Hanrahan, P., Huang, Q., Li, Z., Savarese, S., Savva, M., Song, S., Su, H., et al.: An information-rich 3D model repository. 1(7), 8 (2015). arXiv preprint
arXiv:1512.03012
4. Chang, A.X., Funkhouser, T., Guibas, L., Hanrahan, P., Huang, Q., Li, Z., Savarese, S., Savva, M., Song, S., Su, H., Xiao, J., Yi, L., Yu, F.: ShapeNet: an information-rich 3D model repository. Technical Report, Stanford University—Princeton University—Toyota Technological Institute at Chicago (2015).
arXiv:1512.03012
[cs.GR]
5. Chen, X., Duan, Y., Houthooft, R., Schulman, J., Sutskever, I., Abbeel, P.: InfoGAN: interpretable representation learning by information maximizing generative adversarial nets. In: Advances in Neural Information Processing Systems, pp. 2172–2180 (2016)