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π€ ShIRE Dataset: 6D Pose Trajectories of Independently Moving Objects
The ShIRE Dataset is the official reference implementation of the method introduced in the paper:
ShIRE: Real-Time 6D Pose Tracking of Independently Moving Objects
Presented at VISAPP 2021
π Overview
ShIRE (Short for Shape-aware Independent Real-time Estimation) is a method for real-time detection and 6D pose trajectory estimation of independently moving objects in dynamic environments.
This dataset accompanies the ShIRE method and is intended to support research and development in:
- 6D object pose estimation
- Multi-object tracking
- Real-time scene understanding
- Robotics and AR/VR applications
π Dataset Structure
The dataset consists of RGB-D video sequences, ground-truth 6D pose annotations, and object segmentation masks for multiple independently moving objects.
shire/
βββ sequences/
β βββ seq01/
β β βββ rgb/
β β βββ depth/
β β βββ poses/
β β βββ masks/
β βββ ...
βββ calibration/
βββ metadata.json
βοΈ Use with Hugging Face Datasets
You can load the ShIRE dataset directly via datasets.load_dataset
:
from datasets import load_dataset
dataset = load_dataset("your-username/shire")
π Citation
If you use the ShIRE dataset or method in your research, please cite:
@inproceedings{Reiss2021ShIRE,
author = {Simon Reiss and JΓΆrg StΓΌckler},
title = {ShIRE: Real-Time 6D Pose Tracking of Independently Moving Objects},
booktitle = {Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP},
year = {2021},
pages = {189-196},
publisher = {INSTICC},
doi = {10.5220/0010254001890196}
}
π§ More Information
- π VISAPP 2021 Paper
- π§ Reference implementation coming soon to Hugging Face Spaces
- π¬ For questions or collaborations, contact the original authors or open an issue in the repo
π License
This dataset is provided for all use. Please review the license included in the dataset files.
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