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**For more details, dataloaders and how to use this dataset**: see our Github repo: https://github.com/zubair-irshad/NeRF-MAE
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Note: The above datasets are all you need to train and evaluate our method. Bonus: we will be releasing our multi-view rendered posed RGB images from FRONT3D, HM3D and Hypersim as well as Instant-NGP trained checkpoints soon (these comprise over 1.6M+ images and 3200+ NeRF checkpoints)
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Please note that our dataset was generated using the instruction from [NeRF-RPN]([NeRF-RPN](https://github.com/lyclyc52/NeRF_RPN)) and [3D-CLR](https://vis-www.cs.umass.edu/3d-clr/). Please consider citing our work, NeRF-RPN and 3D-CLR if you find this dataset useful in your research.
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**For more details, dataloaders and how to use this dataset**: see our Github repo: https://github.com/zubair-irshad/NeRF-MAE
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**Coming Soon**: Multi-view rendered images and Instant-NGP checkpoints (totalling 3200+ trained NeRF checkpoints and over 1M images)
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Note: The above datasets are all you need to train and evaluate our method. Bonus: we will be releasing our multi-view rendered posed RGB images from FRONT3D, HM3D and Hypersim as well as Instant-NGP trained checkpoints soon (these comprise over 1.6M+ images and 3200+ NeRF checkpoints)
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Please note that our dataset was generated using the instruction from [NeRF-RPN]([NeRF-RPN](https://github.com/lyclyc52/NeRF_RPN)) and [3D-CLR](https://vis-www.cs.umass.edu/3d-clr/). Please consider citing our work, NeRF-RPN and 3D-CLR if you find this dataset useful in your research.
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