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mingyang-wu/Objectron-Videos

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Hugging Face2026-04-02 更新2026-04-12 收录
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https://hf-mirror.com/datasets/mingyang-wu/Objectron-Videos
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# Objectron Videos Mirror This repository is a videos-only mirror of the official Objectron dataset, prepared for hosting on Hugging Face. 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. 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 The video files follow the official Objectron layout pattern: - `videos/class/batch-i/j/video.MOV` 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/). Objectron is a large-scale, object-centric video dataset with pose annotations and has made important contributions to 3D understanding and related vision research. 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 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} } ``` 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}, } ```
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