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Hypernetwork → Shape pipeline checkpoints

Trained models and processed data for image-to-3D experiments documented at BOB-THE-BUILDER-in/Hypernetwork.

Contents

  • tier_essential.tar.gz (1.98 GB) — anchors, autoencoder, mappers, results
  • tier_data.tar.gz (2.67 GB) — watertight meshes, SDF samples, image-SIRENs, shape-SIRENs
  • tier_hypernets.tar.gz (6.69 GB) — 100 trained hypernets (one per training shape)

Source

Mesh data derived from Objaverse 1.0. Individual creators retain rights to original models.

Restore

See the GitHub repo's README for full restoration instructions.

Key results

  • Direct weight prediction (264K-dim) at N=100 produces fragmented OOD predictions
  • Latent autoencoder compression to 128 dims rescues OOD generalization
  • Mapper from hypernet → 128-dim latent achieves MSE 1.4e-5 with 9M× scrambled-cond ratio
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