3D Reconstruction of Incomplete Archaeological Objects Using a Generative Adversarial Network

Author:

Hermoza Renato1,Sipiran Ivan1

Affiliation:

1. Pontifical Catholic University of Peru, Lima, Peru

Publisher

ACM Press

Reference31 articles.

1. Martin Arjovsky, Soumith Chintala, and LÃlon Bottou. 2017. Wasserstein GAN. arXiv:1701.07875 [cs, stat] (Jan. 2017). http://arxiv.org/abs/1701.07875 arXiv: 1701.07875.

2. Angel X. Chang, Thomas Funkhouser, Leonidas Guibas, Pat Hanrahan, Qixing Huang, Zimo Li, Silvio Savarese, Manolis Savva, Shuran Song, Hao Su, Jianxiong Xiao, Li Yi, and Fisher Yu. 2015. ShapeNet: An Information-Rich 3D Model Repository. Technical Report arXiv:1512.03012 [cs.GR]. Stanford University âĂŤ Princeton University âĂŤ Toyota Technological Institute at Chicago.

3. FranÃğois Chollet and others. 2015. Keras. https://github.com/fchollet/keras (2015). https://github.com/fchollet/keras

4. Angela Dai, Charles Ruizhongtai Qi, and Matthias Nieçner. 2016. Shape Completion using 3D-Encoder-Predictor CNNs and Shape Synthesis. arXiv:1612.00101 [cs] (Nov. 2016). http://arxiv.org/abs/1612.00101 arXiv: 1612.00101.

5. Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. 2014. 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., 2672--2680. http://papers.nips.cc/paper/5423-generative-adversarial-nets.pdf

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