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yupengchengg147/St4RTrack
St4RTrack is a image-to-3d model from yupengchengg147. Use it for the image-to-3d task on the model card, and read the license before you ship it in a product. It is set up for dust3r.
Github page: https://github.com/HavenFeng/St4RTrack Project page: https://st4rtrack.github.io/ Paper: https://arxiv.org/abs/2504.13152
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From the Hugging Face model README
@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}
}
Github page: https://github.com/HavenFeng/St4RTrack
Project page: https://st4rtrack.github.io/
Paper: https://arxiv.org/abs/2504.13152
First install St4rTrack. To load the model (Seq):
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:
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)