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CHANGELOG.md

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The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/)
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and this project adheres to [Semantic Versioning](http://semver.org/spec/v2.0.0.html).
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## [1.1.0] - 2023-05-28
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### Changed
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- Optimized network evaluation shader code (thanks to [@mrxz](https://github.com/mrxz))
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## [1.0.1] - 2023-04-07
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### Changed

package.json

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{
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"name": "com.doji.mobilenerf",
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"version": "1.0.1",
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"version": "1.1.0",
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"displayName": "MobileNeRF",
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"description": "An unofficial Unity port of the MobileNeRF viewer.",
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"dependencies":

readme.md

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### Importing sample scenes
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After succesful installation, you can use the menu *MobileNeRF -> Asset Downloads* to download any of the sample scenes available.
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After succesful installation, you can use the menu `MobileNeRF -> Asset Downloads` to download any of the sample scenes available.
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In each scene folder there will be a convenient prefab, that you can then drag into the scene and you're good to go.
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### Updating
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Since the initial release a small number of features have been added to the automatic shader generation code.
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That means, that if you have already downloaded some scenes before, you'll have to regenerate the source files by going to *MobileNeRF -> Asset Downloads* again.
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That means, that if you have already downloaded some scenes before, you'll have to regenerate the source files by going to `MobileNeRF -> Asset Downloads` again.
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(This will not actually redownload Assets unless necessary, so this shouldn't take too long)
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### Importing self-trained scenes
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* Forward Rendering, but do a Depth Prepass to reduce overdraw (might require URP, see [here](https://forum.unity.com/threads/need-clarification-on-urps-use-of-the-depth-prepass.1004577/) and [here](https://gist.github.com/aras-p/5e3aa6f81c543ca74e3ae296c72ffcaf))
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* Implement Deferred Rendering and compare performance in various scenarios
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More details can be found in the official paper linked below.
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## Known Issues
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- Does not work well with MSAA. For now, I recommend turning MSAA off in `Project Settings -> Quality -> Anti Aliasing`
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## Acknowledgements
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Thanks to
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- [@mrxz](https://github.com/mrxz) for providing some major performance optimizations as part of his [WebXR port](https://github.com/mrxz/mobilenerf-viewer-webxr)
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[^1]: [Zhiqin Chen and Thomas Funkhouser and Peter Hedman and Andrea Tagliasacchi. MobileNeRF: Exploiting the Polygon Rasterization Pipeline for Efficient Neural Field Rendering on Mobile Architectures. arXiv preprint arXiv:2208.00277, 2022](https://mobile-nerf.github.io/)

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