| | --- |
| | license: mit |
| | pipeline_tag: text-to-3d |
| | tags: |
| | - image-to-3d |
| | - text-to-3d |
| | - 'pokemon ' |
| | - realistic |
| | - fantasy |
| | - technology |
| | --- |
| | |
| | # LGM |
| |
|
| | This model contains the pretrained weights for *LGM: Large Multi-View Gaussian Model for High-Resolution 3D Content Creation*. |
| |
|
| | ### [Project Page](https://me.kiui.moe/lgm/) | [Arxiv](https://arxiv.org/abs/2402.05054) | [Weights](https://huggingface.co/ashawkey/LGM) |
| |
|
| |
|
| | ## Introduction |
| | LGM can generate 3D objects from image or text within 5 seconds at high-resolution based on Gaussian Splatting. |
| |
|
| | <video controls autoplay src="https://cdn-uploads.huggingface.co/production/uploads/63367f9a9895307563659be6/9CVJZ5ZXkhheDPKl3M0pM.mp4"></video> |
| |
|
| | <video controls autoplay src="https://cdn-uploads.huggingface.co/production/uploads/63367f9a9895307563659be6/6DM_hNEDLRJOz95pgVjek.mp4"></video> |
| |
|
| |
|
| | ## Model Details |
| | The model is trained on a ~80K subset of [Objaverse](https://huggingface.co/datasets/allenai/objaverse). |
| | For more details, please refer to our paper. |
| |
|
| | ## Usage |
| |
|
| | To download the model: |
| | ```python |
| | from huggingface_hub import hf_hub_download |
| | ckpt_path = hf_hub_download(repo_id="ashawkey/LGM", filename="model_fp16.safetensors") |
| | ``` |
| | Please refer to our [repo](https://github.com/3DTopia/LGM) for more details on loading and inference. |
| |
|
| | ## Citation |
| |
|
| | ``` |
| | @article{tang2024lgm, |
| | title={LGM: Large Multi-View Gaussian Model for High-Resolution 3D Content Creation}, |
| | author={Tang, Jiaxiang and Chen, Zhaoxi and Chen, Xiaokang and Wang, Tengfei and Zeng, Gang and Liu, Ziwei}, |
| | journal={arXiv preprint arXiv:2402.05054}, |
| | year={2024} |
| | } |
| | ``` |
