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bobthebuilderinternational/hypernet-prior-topic03

Hypernet — Prior Topic 03 Archive Complete archive of the prior topic 03 research thread: per-shape SIREN decoders, per-layer hypernetwork architectures, mapper experiments, and ancillary checkpoints. This work predates the current image-to-3D pipeline documented in hypernet-image-to-3d and the main dataset. 100 shapes, naming convention obj_NN for NN in [0..99]. Contents Path Size Description watertight/ ~5.6 GB 100 watertight .obj meshes (filename… See the full description on the dataset page: https://huggingface.co/datasets/bobthebuilderinternational/hypernet-prior-topic03.

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Hypernet — Prior Topic 03 Archive

Complete archive of the prior topic 03 research thread: per-shape SIREN decoders, per-layer hypernetwork architectures, mapper experiments, and ancillary checkpoints. This work predates the current image-to-3D pipeline documented in hypernet-image-to-3d and the main dataset.

100 shapes, naming convention obj_NN for NN in [0..99].

Contents

PathSizeDescription
watertight/~5.6 GB100 watertight .obj meshes (filename obj_NN.obj)
sdf_samples/~591 MB100 .npz files with point/SDF pairs
shape_sirens/~505 MB100 trained per-shape SIREN decoders + reconstructions in meshes_w30/
hypernets/~6.7 GB100 trained per-shape hypernetworks (full weight space)
image_sirens/~629 MB2400 image-SIREN files (24 views × 100 shapes)
checkpoints/~220 MBVAE, direct-mapper, and h90 variant checkpoints
diagnostics/~1 MBTraining diagnostic plots and metric dumps
hypernet_meshes/~188 MBSample reconstructions from trained hypernets

Note on naming

The corresponding folder in the source repo was named sdf_samples_old10; it has been renamed to sdf_samples here for clarity. The _old10 suffix was a local distinguisher when this codebase ran alongside other variants.

Citation

Jain, A. (2026). Hypernet research archive — prior topic 03 (per-shape hypernetworks
and SIREN decoders). HuggingFace: bobthebuilderinternational/hypernet-prior-topic03.

License

Apache 2.0. Underlying meshes are derived from publicly available sources under their own licenses.