| # Objectron Videos Mirror |
|
|
| This repository is a videos-only mirror of the official Objectron dataset, prepared for hosting on Hugging Face. |
|
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| Official source repository: |
| - https://github.com/google-research-datasets/Objectron |
|
|
| ## Purpose |
|
|
| - Provide a clean and upload-friendly copy of Objectron video files. |
| - Keep directory layout aligned with official dataset conventions. |
| - Simplify distribution for downstream training and research workflows. |
|
|
| ## What Is Included |
|
|
| This mirror currently contains only video files. |
|
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| Included: |
| - `videos/<class>/batch-<i>/<j>/<video>.MOV` |
|
|
| Not included in this mirror: |
| - annotation protobufs (for example `geometry.pbdata`) |
| - AR metadata protobufs |
| - tf.records / sequence examples |
| - index files and train/test split files |
| - parsing/evaluation scripts |
|
|
| For full dataset assets and tooling, use the official repository and storage paths. |
|
|
| ## Directory Layout |
|
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| The video files follow the official Objectron layout pattern: |
|
|
| - `videos/class/batch-i/j/video.MOV` |
|
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| Current class folders may include: |
| - `bike` |
| - `book` |
| - `bottle` |
| - `camera` |
| - `cereal_box` |
| - `chair` |
| - `cup` |
| - `laptop` |
| - `shoe` |
|
|
| ## License |
|
|
| This repository follows the official Objectron licensing terms. |
|
|
| Objectron is released under: |
| - Computational Use of Data Agreement 1.0 (C-UDA-1.0) |
| - https://github.com/microsoft/Computational-Use-of-Data-Agreement |
|
|
| A copy of the license is included in [LICENSE](LICENSE). |
|
|
| ## Attribution |
|
|
| If you use Objectron data, please cite the official Objectron paper and follow attribution guidance from the official repository: |
| - https://github.com/google-research-datasets/Objectron |
|
|
| ## Acknowledgment |
|
|
| We thank the Objectron team and the official maintainers for providing this dataset and related resources. These contributions were instrumental in the successful completion of our work: [ConsID-Gen](https://mingyang.me/ConsID-Gen/). |
|
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| Objectron is a large-scale, object-centric video dataset with pose annotations and has made important contributions to 3D understanding and related vision research. |
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| This repository is only a videos-only mirror for easier access and distribution. |
|
|
| ## Disclaimer |
|
|
| - This repository is not an official Google release. |
| - We cannot guarantee that the number of videos in this mirror exactly matches the counts reported in the original Objectron paper or official storage. |
| - The contents here only include video files available from our local download process. |
|
|
| ## Citation |
|
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| If you found the original Objectron dataset useful, please cite the official paper. |
|
|
| ```bibtex |
| @article{objectron2021, |
| title={Objectron: A Large Scale Dataset of Object-Centric Videos in the Wild with Pose Annotations}, |
| author={Adel Ahmadyan, Liangkai Zhang, Artsiom Ablavatski, Jianing Wei, Matthias Grundmann}, |
| journal={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition}, |
| year={2021} |
| } |
| ``` |
|
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| This is not an officially supported Google product. If you have any question, you can email us at objectron@google.com or join our mailing list at objectron@googlegroups.com. |
|
|
| ```bibtex |
| @misc{wu2026considgenviewconsistentidentitypreservingimagetovideo, |
| title={ConsID-Gen: View-Consistent and Identity-Preserving Image-to-Video Generation}, |
| author={Mingyang Wu and Ashirbad Mishra and Soumik Dey and Shuo Xing and Naveen Ravipati and Hansi Wu and Binbin Li and Zhengzhong Tu}, |
| year={2026}, |
| eprint={2602.10113}, |
| archivePrefix={arXiv}, |
| primaryClass={cs.CV}, |
| url={https://arxiv.org/abs/2602.10113}, |
| } |
| ``` |
|
|
