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U4D: Uncertainty-Aware 4D World Modeling from LiDAR Sequences

Xiang Xu     Ao Liang     Youquan Liu     Linfeng Li     Lingdong Kong     Ziwei Liu     Qingshan Liu    

     

In this work, we introduce U4D, an uncertainty-aware framework for 4D LiDAR world modeling. The main contributes are:

• We introduce the first uncertainty-aware LiDAR generation framework that explicitly models spatial difficulty to enhance reliability in 4D world modeling.
• We design a two-stage hard-to-easy generation paradigm that reconstructs uncertain regions first and then completes the full scene under these priors.
• We develop a Mixture of Spatio-Temporal (MoST) block that ensures temporal consistency across frames by adaptively balancing spatial geometry and temporal dynamics.

📚 Citation

If you find this work helpful for your research, please kindly consider citing our paper:

@article{xu2025U4D,
    title   = {{U4D}: Uncertainty-Aware {4D} World Modeling from LiDAR Sequences},
    author  = {Xu, Xiang and Liang, Ao and Liu, Youquan and Li, Linfeng and Kong, Lingdong and Liu, Ziwei and Liu, Qingshan},
    journal = {arXiv preprint arXiv: 2512.02982},
    year    = {2025}
}

Updates

• [12.2025] - The technical report of U4D is available on arXiv.

License

This work is under the Apache License Version 2.0, while some specific implementations in this codebase might be with other licenses. Kindly refer to LICENSE.md for a more careful check, if you are using our code for commercial matters.

Acknowledgements

This work is developed based on the R2DM codebase.