CoTracker3_Kubric

# Kubric Dataset for CoTracker 3

## Overview
This dataset was specifically created for training CoTracker 3, a state-of-the-art point tracking model. The dataset was generated using the Kubric engine.

## Dataset Specifications
- **Size**: ~6,000 sequences
- **Resolution**: 512×512 pixels
- **Sequence Length**: 120 frames per sequence
- **Camera Movement**: Carefully rendered with subtle camera motion to simulate realistic scenarios
- **Format**: Generated using Kubric engine

## Usage
The dataset can be parsed using the official CoTracker implementation. For detailed parsing instructions, refer to:
- [CoTracker Dataset Parser](https://github.com/facebookresearch/co-tracker/blob/main/cotracker/datasets/kubric_movif_dataset.py)
- [Kubric Engine Repository](https://github.com/google-research/kubric)

## Citation

If you use this dataset in your research, please cite the following papers:

```bibtex
@inproceedings{karaev24cotracker3,
title = {CoTracker3: Simpler and Better Point Tracking by Pseudo-Labelling Real Videos},
author = {Nikita Karaev and Iurii Makarov and Jianyuan Wang and Natalia Neverova and Andrea Vedaldi and Christian Rupprecht},
booktitle = {Proc. {arXiv:2410.11831}},
year = {2024}
}
```

```bibtex
@article{greff2021kubric,
title = {Kubric: a scalable dataset generator},
author = {Klaus Greff and Francois Belletti and Lucas Beyer and Carl Doersch and
Yilun Du and Daniel Duckworth and David J Fleet and Dan Gnanapragasam and
Florian Golemo and Charles Herrmann and Thomas Kipf and Abhijit Kundu and
Dmitry Lagun and Issam Laradji and Hsueh-Ti (Derek) Liu and Henning Meyer and
Yishu Miao and Derek Nowrouzezahrai and Cengiz Oztireli and Etienne Pot and
Noha Radwan and Daniel Rebain and Sara Sabour and Mehdi S. M. Sajjadi and Matan Sela and
Vincent Sitzmann and Austin Stone and Deqing Sun and Suhani Vora and Ziyu Wang and
Tianhao Wu and Kwang Moo Yi and Fangcheng Zhong and Andrea Tagliasacchi},
booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2022},
}
```

# 用于CoTracker 3的Kubric数据集

## 概述
本数据集专为训练当前最先进的点跟踪模型CoTracker 3而打造，全程通过Kubric引擎生成。

## 数据集规格
- **规模**：约6000个序列
- **分辨率**：512×512像素
- **序列长度**：每个序列包含120帧
- **相机运动**：经精细渲染，采用细微的相机运动以模拟真实场景
- **数据格式**：基于Kubric引擎生成

## 使用说明
本数据集可通过官方CoTracker实现代码进行解析。如需获取详细的解析操作指南，请参考以下链接：
- [CoTracker数据集解析器](https://github.com/facebookresearch/co-tracker/blob/main/cotracker/datasets/kubric_movif_dataset.py)
- [Kubric引擎开源仓库](https://github.com/google-research/kubric)

## 引用规范
若您在研究工作中使用本数据集，请引用如下论文：
bibtex
@inproceedings{karaev24cotracker3,
title = {CoTracker3: Simpler and Better Point Tracking by Pseudo-Labelling Real Videos},
author = {Nikita Karaev and Iurii Makarov and Jianyuan Wang and Natalia Neverova and Andrea Vedaldi and Christian Rupprecht},
booktitle = {Proc. {arXiv:2410.11831}},
year = {2024}
}

bibtex
@article{greff2021kubric,
title = {Kubric: a scalable dataset generator},
author = {Klaus Greff and Francois Belletti and Lucas Beyer and Carl Doersch and Yilun Du and Daniel Duckworth and David J Fleet and Dan Gnanapragasam and Florian Golemo and Charles Herrmann and Thomas Kipf and Abhijit Kundu and Dmitry Lagun and Issam Laradji and Hsueh-Ti (Derek) Liu and Henning Meyer and Yishu Miao and Derek Nowrouzezahrai and Cengiz Oztireli and Etienne Pot and Noha Radwan and Daniel Rebain and Sara Sabour and Mehdi S. M. Sajjadi and Matan Sela and Vincent Sitzmann and Austin Stone and Deqing Sun and Suhani Vora and Ziyu Wang and Tianhao Wu and Kwang Moo Yi and Fangcheng Zhong and Andrea Tagliasacchi},
booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2022},
}