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STARCaster: Spatio-Temporal AutoRegressive Video Diffusion for Identity- and View-Aware Talking Portraits

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# STARCaster: Spatio-Temporal AutoRegressive Video Diffusion for Identity- and View-Aware Talking Portraits

[Foivos Paraperas Papantoniou](https://foivospar.github.io/)1 &emsp; [Stathis Galanakis](https://stathisgln.github.io/)1 &emsp; [Rolandos Alexandros Potamias](https://rolpotamias.github.io/)1

[Bernhard Kainz](https://bernhard-kainz.com/)1,2 &emsp; [Stefanos Zafeiriou](https://www.imperial.ac.uk/people/s.zafeiriou)1

1Imperial College London, UK &emsp; 2FAU Erlangen-Nürnberg, Germany

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**[STARCaster](https://foivospar.github.io/STARCaster/)** is a spatio-temporal autoregressive video diffusion framework for speech-driven portrait animation and continuous view synthesis. Leveraging strong identity guidance, it further supports subject-consistent yet reference-free talking portraits, allowing recontextualization beyond the constraints of the input image.

# 🔔 News/Updates

- **[Dec 2025]** Paper released on arXiv.
- **Code & pretrained models** will be released soon. Stay tuned!

# 📝 Citation
If you find STARCaster useful for your research, please consider citing us:

```bibtex
@article{paraperas2025starcaster,
      title={STARCaster: Spatio-Temporal AutoRegressive Video Diffusion for Identity- and View-Aware Talking Portraits}, 
      author={Paraperas Papantoniou, Foivos and Galanakis, Stathis and Potamias, Rolandos Alexandros and Kainz, Bernhard and Zafeiriou, Stefanos},
      journal={arXiv preprint arXiv:2512.13247},
      year={2025}
}
```

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