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- license: cc-by-nc-sa-4.0
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+ ---
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+ license: cc-by-nc-sa-4.0
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+ ---
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+
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+ # 4DGT Model Card
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+
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+ ## Model Details
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+
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+ 4DGT (4D Gaussian Transformer) is a neural network model that learns dynamic 3D Gaussian representations from monocular videos. It uses a transformer-based architecture to predict 4D Gaussians from a dynamic scenes observed from an egocentric video.
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+ - **Paper:** [4DGT: Learning a 4D Gaussian Transformer Using Real-World Monocular Videos](https://arxiv.org/abs/2506.08015)
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+ - **Project Page:** [https://4dgt.github.io/](https://4dgt.github.io/)
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+ - **Github:** [GitHub repository](https://github.com/facebookresearch/4dgt)
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+ Please refer to the project page and github for more details of the model.
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+ ## Citation
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+ ```bibtex
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+ @inproceedings{xu20254dgt,
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+ title = {4DGT: Learning a 4D Gaussian Transformer Using Real-World Monocular Videos},
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+ author = {Xu, Zhen and Li, Zhengqin and Dong, Zhao and Zhou, Xiaowei and Newcombe, Richard and Lv, Zhaoyang},
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+ journal = {arXiv preprint arXiv:2506.08015},
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+ year = {2025}
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+ }
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+ ```
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+
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+ ## Model Files
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+
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+ ### Checkpoint: `4dgt_full.pth`
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+ - **Size:** ~14.5 GB
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+ - **Format:** PyTorch state dict
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+ - **Contents:**
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+ - The full model trained as described in the paper.
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+ - Encoder weights (DINOv2 backbone)
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+ - Level of Details Transformer
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+ - 4D Gaussian Decoder
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+
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+ ### Checkpoint: `4dgt_1st_stage.pth`
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+ - **Size:** ~4.85 GB
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+ - **Format:** PyTorch state dict
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+ - **Contents:**
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+ - The first stage model trained only using Egoexo4D dataset as described in the paper.
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+ - Encoder weights (DINOv2 backbone)
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+ - Vanilla Transformer, no level of details.
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+ - 4D Gaussian Decoder
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+
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+ ## Quick Start
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+ Please refer to [4DGT GitHub repository](https://github.com/facebookresearch/4dgt) for the full set up.
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+
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+ ## Contact
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+ For questions and issues, please open an issue on the [GitHub repository](https://github.com/facebookresearch/4dgt).