Making the natural treasures of our world accessible to everyone. The project will take 2d images of natural scenes, and attempt to texture 3d Unity environments, using a complex of machine learning approaches for interpolating texture and depth from static images.
- https://medium.com/towards-data-science/neural-networks-and-the-future-of-3d-procedural-content-generation-a2132487d44a - "Knowing that, I went over to http://terrain.party, a website where you can download elevation data from the Earth."
https://github.com/jiajunwu/3dinn - "Wu, J., Xue, T., Lim, J. J., Tian, Y., Tenenbaum, J. B., Torralba, A., & Freeman, W. T. (2016). Single image 3D interpreter network. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9910 LNCS). http://doi.org/10.1007/978-3-319-46466-4_22"
https://arxiv.org/abs/1811.07605 sparse 3d to 3d point cloud
Eric Guérin, Julie Digne, Eric Galin, Adrien Peytavie, Christian Wolf, et al.. Interactive Example- Based Terrain Authoring with Conditional Generative Adversarial Networks. Transactions on Graph- ics (Proceedings of Siggraph Asia 2017), ACM, 2017, 36, pp.228 - 228. <10.1145/3130800.3130804>.
BBC Earth - Live in VR - https://www.youtube.com/watch?v=k9OkENZwzL4
- Conduct a test of texture application in Unity: https://www.youtube.com/watch?v=kyHGAwoJIWQ
- Add the Unity project as a subtree
- Designate an appropiate repository for large binary files.
- Decide on 360 video recommendations:
- Decide on how to license work
- How to build on existing work?