Instructions to use google/tapnet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/tapnet with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("google/tapnet", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Fix TAPNext citation: arXiv -> ICCV 2025
Browse files
README.md
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@@ -159,13 +159,14 @@ If you use these models, please cite the relevant papers:
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</details>
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<details>
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<summary>TAPNext (2025)</summary>
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```bibtex
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@
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title={
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author={Zholus, Artem and Doersch, Carl and Yang, Yi and Koppula, Skanda and Patraucean, Viorica and He, Xu Owen and Rocco, Ignacio and Sajjadi, Mehdi
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year={2025}
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}
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```
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</details>
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<details>
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<summary>TAPNext (ICCV 2025)</summary>
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```bibtex
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@inproceedings{zholus2025tapnext,
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title={Tapnext: Tracking any point (tap) as next token prediction},
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author={Zholus, Artem and Doersch, Carl and Yang, Yi and Koppula, Skanda and Patraucean, Viorica and He, Xu Owen and Rocco, Ignacio and Sajjadi, Mehdi SM and Chandar, Sarath and Goroshin, Ross},
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booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
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pages={9693--9703},
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year={2025}
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}
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```
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