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Update README.md with first successful Neural Implicit Representation… #9

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Expand Up @@ -75,8 +75,9 @@ imitation tasks.

# Papers
## Implicit Neural Representations of Geometry
The following three papers first (and concurrently) demonstrated that implicit neural representations outperform grid-, point-, and mesh-based
The following four papers first (and concurrently) demonstrated that implicit neural representations outperform grid-, point-, and mesh-based
representations in parameterizing geometry and seamlessly allow for learning priors over shapes.
* [Hypernetwork functional image representation](https://arxiv.org/pdf/1902.10404.pdf) (Klocek et al. 2019)
* [DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation](https://arxiv.org/abs/1901.05103) (Park et al. 2019)
* [Occupancy Networks: Learning 3D Reconstruction in Function Space](https://arxiv.org/abs/1812.03828) (Mescheder et al. 2019)
* [IM-Net: Learning Implicit Fields for Generative Shape Modeling](https://arxiv.org/abs/1812.02822) (Chen et al. 2018)
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