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README.md
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@@ -436,6 +436,8 @@ neural representations / neural fields on 3D shapes.
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This dataset is shared as part of the CVPR 2026 paper [Weight Space Representation Learning via Neural Field Adaptaion](https://arxiv.org/abs/2512.01759).
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Code for producing this dataset is shared in the [wsr.pytorch](https://github.com/IVRL/wsr.pytorch) neural-field codebase.
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Each shape is converted into a watertight manifold, normalized into the unit
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cube `[-1, 1]³`, and sampled into three point sets (`uniform`, `surface`,
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`groundtruth`), each stored as a `[N, 4]` `float32` array of `[x, y, z, sdf]`.
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This dataset is shared as part of the CVPR 2026 paper [Weight Space Representation Learning via Neural Field Adaptaion](https://arxiv.org/abs/2512.01759).
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Code for producing this dataset is shared in the [wsr.pytorch](https://github.com/IVRL/wsr.pytorch) neural-field codebase.
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<img src="https://inrainbws.github.io/assets/images/wsrl.png" width="640">
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Each shape is converted into a watertight manifold, normalized into the unit
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cube `[-1, 1]³`, and sampled into three point sets (`uniform`, `surface`,
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`groundtruth`), each stored as a `[N, 4]` `float32` array of `[x, y, z, sdf]`.
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