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arXiv AI By Haoran Xu, Peixi Peng, Shijun Guo, Guang Tan, Yiqian Chang, Yisen Zhao, Shuaixian Wang, Yonghong Tian

Aligned Delta-Triplane Transformers as Occupancy World Models

Read the original on arXiv AI →

The paper introduces Aligned Delta-Triplane Transformers (ADTT), a compact 4D Occupancy World Model that explicitly aligns historical triplanes with ego-motion compensation and predicts only future scene changes. By using a query-conditioned Transformer to predict residual changes guided by ego-motion and external queries, ADTT adds these changes to the aligned prior and decodes them into future occupancy scenes. Experiments on Occ3D-nus demonstrate that ADTT achieves state‑of‑the‑art forecasting performance with fewer parameters and higher FPS.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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