St4RTrack

--- library_name: dust3r tags: - image-to-3d - model_hub_mixin - pytorch_model_hub_mixin --- # St4RTrack: Simultaneous 4D Reconstruction and Tracking in the World ```bibtex @inproceedings{st4rtrack2025, title={St4RTrack: Simultaneous 4D Reconstruction and Tracking in the World}, author={Feng*, Haiwen and Zhang*, Junyi and Wang, Qianqian and Ye, Yufei and Yu, Pengcheng and Black, Michael J. and Darrell, Trevor and Kanazawa, Angjoo}, booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision}, year={2025} } ``` ## Model info Github page: https://github.com/HavenFeng/St4RTrack Project page: https://st4rtrack.github.io/ Paper: https://arxiv.org/abs/2504.13152 ## How to Use First install [St4rTrack](https://github.com/HavenFeng/St4RTrack). To load the model (Seq): ```python from dust3r.models import AsymmetricCroCo3DStereo # Loads default Seq checkpoint model = AsymmetricCroCo3DStereo.from_pretrained("yupengchengg147/St4RTrack") ``` Run the following code to load the checkpoint trained with Pair Mode: ```python from huggingface_hub import hf_hub_download import tempfile import os from dust3r.model import AsymmetricCroCo3DStereo # Create a temporary directory for the model files temp_dir = os.path.join(tempfile.gettempdir(), "St4RTrack_pair") os.makedirs(temp_dir, exist_ok=True) # Download the config and model files from the Pair subfolder config_path = hf_hub_download( repo_id="yupengchengg147/St4RTrack", filename="Pair/config.json", cache_dir=temp_dir ) # Load the model from the downloaded path model_dir = os.path.dirname(config_path) model = AsymmetricCroCo3DStereo.from_pretrained(model_dir) ```

Source context: 443 downloads · 0 likes · Pipeline image-to-3d · Library dust3r · Repo yupengchengg147/St4RTrack