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@@ -3,7 +3,7 @@ Neural Radiance Fields in PyTorch3D
This project implements the Neural Radiance Fields (NeRF) from [1].
-
+
Installation
@@ -77,6 +77,16 @@ https://dl.fbaipublicfiles.com/pytorch3d_nerf_data
Attribution: `lego` and `fern` are data from the original code release of [1] in https://drive.google.com/drive/folders/128yBriW1IG_3NJ5Rp7APSTZsJqdJdfc1, which are hosted under the CC-BY license (https://creativecommons.org/licenses/by/4.0/) The S3 bucket files contains the same images while the camera matrices have been adjusted to follow the PyTorch3D convention.
+#### Quantitative results
+Below are the comparisons between our implementation and the official [`TensorFlow code`](https://github.com/bmild/nerf). The speed is measured on NVidia Quadro GP100.
+```
++----------------+------------------+------------------+-----------------+
+| Implementation | Lego: test PSNR | Fern: test PSNR | training speed |
++----------------+------------------+------------------+-----------------+
+| TF (official) | 31.0 | 27.5 | 0.24 sec/it |
+| PyTorch3D | 32.7 | 27.9 | 0.18 sec/it |
++----------------+------------------+------------------+-----------------+
+```
#### References
[1] Ben Mildenhall and Pratul P. Srinivasan and Matthew Tancik and Jonathan T. Barron and Ravi Ramamoorthi and Ren Ng, NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis, ECCV2020