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OMMO
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OMMO
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# OMMO ### A Large-scale <font color="#006600">O</font>utdoor <font color="#006600">M</font>ulti-<font color="#006600">m</font><font color="#006600">o</font>dal Dataset and Benchmark for Novel View Synthesis and Implicit Scene Reconstrcution ### [Project Page](https://ommo.luchongshan.com/) | [Arxiv](https://arxiv.org/abs/2301.06782) ## 🚩 News Released the pre version of ommo dataset at 2023/01/27,some content remaining to be updated and uploaded ## [Demo Video](https://www.loom.com/share/7b9ed35bfb3649eda051398d3a51cda7) ## Download ### [data link](https://drive.google.com/drive/folders/1Nu_xD4CUc_1f2YKEbdZP-nfbzyI3na7m?usp=sharing) Note:Some of scene data are not the highest resloution version for quick access to our dataset, this part will be replaced asap. ## Citation ``` @article{lu2023large, title={A Large-Scale Outdoor Multi-modal Dataset and Benchmark for Novel View Synthesis and Implicit Scene Reconstruction}, author={Lu, Chongshan and Yin, Fukun and Chen, Xin and Chen, Tao and Yu, Gang and Fan, Jiayuan}, journal={arXiv preprint arXiv:2301.06782}, year={2023} } ``` <!-- ### [checkpoints] ## Acknowledgments --> ## License This code is distributed under an [MIT LICENSE](LICENSE).
