| # 3DIEBench-OOD | |
| Out-of-distribution (OOD) test set for [3DIEBench](https://github.com/facebookresearch/SIE/tree/main/data), designed to evaluate equivariance generalization to unseen rotation ranges. | |
| ## Dataset Description | |
| 3DIEBench-OOD contains rendered views of ShapeNet objects with rotations sampled from ranges **not seen during training**: | |
| | | Training (3DIEBench) | OOD Test (This Dataset) | | |
| |---|---|---| | |
| | **Rotation Range** | [-π/2, π/2] | [-π, -π/2] ∪ [π/2, π] | | |
| This allows testing whether models can extrapolate equivariant predictions to OOD rotation angles. | |
| For generation details, see [`data/3DIEBench/data_generate_ood.py`](https://github.com/hafezgh/seq-jepa/blob/main/seq-jepa/data/3DIEBench/data_generate_ood.py) in the seq-JEPA repository. | |
| ### Structure | |
| | File | Description | | |
| |------|-------------| | |
| | `{synset}/{obj}/image_{i}.jpg` | Rendered image (256×256) | | |
| | `{synset}/{obj}/latent_{i}.npy` | 7D latent vector: [yaw, pitch, roll, floor_hue, spot_θ, spot_φ, spot_hue] | | |
| ## Usage | |
| import numpy as np | |
| from PIL import Image | |
| img = Image.open('04330267/8ff18f81de484792f0b94599b4efe81/image_2.jpg') | |
| latent = np.load('04330267/8ff18f81de484792f0b94599b4efe81/latent_2.npy') | |
| # latent = [yaw, pitch, roll, floor_hue, spot_theta, spot_phi, spot_hue]## Related Resources | |
| - **seq-JEPA Code**: [GitHub](https://github.com/hafezgh/seq-jepa) | |
| - **Project Page**: [hafezgh.github.io/seq-jepa](https://hafezgh.github.io/seq-jepa/) | |
| - **Original 3DIEBench**: [SIE Repository](https://github.com/facebookresearch/SIE/tree/main/data) | |
| ## Citation | |
| If you use this dataset, please cite: | |
| @inproceedings{ghaemi2025seqjepa, | |
| title={seq-{JEPA}: Autoregressive Predictive Learning of Invariant-Equivariant World Models}, | |
| author={Ghaemi, Hafez and Muller, Eilif Benjamin and Bakhtiari, Shahab}, | |
| booktitle={The Thirty-ninth Annual Conference on Neural Information Processing Systems}, | |
| year={2025}, | |
| url={https://openreview.net/forum?id=GKt3VRaCU1} | |
| } | |
| @inproceedings{garrido2024sie, | |
| title={Self-supervised learning of split invariant equivariant representations}, | |
| author={Garrido, Quentin and Balestriero, Randall and Najman, Laurent and LeCun, Yann}, | |
| booktitle={International Conference on Machine Learning}, | |
| year={2024} | |
| } |