Neural nets for “implicit representations”



TBD. See Tancik et al. (2020).

References

Chen, Zhiqin, and Hao Zhang. 2018. “Learning Implicit Fields for Generative Shape Modeling,” December. https://arxiv.org/abs/1812.02822v5.
Mescheder, Lars, Michael Oechsle, Michael Niemeyer, Sebastian Nowozin, and Andreas Geiger. 2018. “Occupancy Networks: Learning 3d Reconstruction in Function Space,” December. https://arxiv.org/abs/1812.03828v2.
Mildenhall, Ben, Pratul P. Srinivasan, Matthew Tancik, Jonathan T. Barron, Ravi Ramamoorthi, and Ren Ng. 2020. “NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis.” arXiv:2003.08934 [Cs], August. http://arxiv.org/abs/2003.08934.
Park, Jeong Joon, Peter Florence, Julian Straub, Richard Newcombe, and Steven Lovegrove. 2019. “DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation,” January. https://arxiv.org/abs/1901.05103v1.
Press, Ofir, Noah A. Smith, and Mike Lewis. 2021. “Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation.” arXiv:2108.12409 [Cs], August. http://arxiv.org/abs/2108.12409.
Sitzmann, Vincent, Julien N. P. Martel, Alexander W. Bergman, David B. Lindell, and Gordon Wetzstein. 2020. “Implicit Neural Representations with Periodic Activation Functions.” arXiv:2006.09661 [Cs, Eess], June. http://arxiv.org/abs/2006.09661.
Sitzmann, Vincent, Michael Zollhoefer, and Gordon Wetzstein. 2019. “Scene Representation Networks: Continuous 3d-Structure-Aware Neural Scene Representations.” Advances in Neural Information Processing Systems 32: 1121–32. https://papers.nips.cc/paper/2019/hash/b5dc4e5d9b495d0196f61d45b26ef33e-Abstract.html.
Stanley, Kenneth O. 2007. “Compositional Pattern Producing Networks: A Novel Abstraction of Development.” Genetic Programming and Evolvable Machines 8 (2): 131–62. https://doi.org/10.1007/s10710-007-9028-8.
Tancik, Matthew, Pratul P. Srinivasan, Ben Mildenhall, Sara Fridovich-Keil, Nithin Raghavan, Utkarsh Singhal, Ravi Ramamoorthi, Jonathan T. Barron, and Ren Ng. 2020. “Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains.” arXiv:2006.10739 [Cs], June. http://arxiv.org/abs/2006.10739.

No comments yet. Why not leave one?

GitHub-flavored Markdown & a sane subset of HTML is supported.