Transformer with Leveraged Masked Autoencoder for video-based Pain Assessment
<|reference_start|>Transformer with Leveraged Masked Autoencoder for video-based Pain Assessment: Accurate pain assessment is crucial in healthcare for effective diagnosis and treatment; however, traditional methods relying on self-reporting are inadequate for populations unable to communicate their pain. Cutting-edge AI is promising for supporting clinicians in pain recognition using facial video data. In this paper, we enhance pain recognition by employing facial video analysis within a Transformer-based deep learning model. By combining a powerful Masked Autoencoder with a Transformers-based classifier, our model effectively captures pain level indicators through both expressions and micro-expressions. We conducted our experiment on the AI4Pain dataset, which produced promising results that pave the way for innovative healthcare solutions that are both comprehensive and objective.<|reference_end|>
@article{nguyen2024transformer,
    title={Transformer with Leveraged Masked Autoencoder for video-based Pain
  Assessment},
    author={Minh-Duc Nguyen, Hyung-Jeong Yang, Soo-Hyung Kim, Ji-Eun Shin, and
  Seung-Won Kim},
    journal={arXiv preprint arXiv:2409.05088},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.05088},
    primaryClass={cs.CV}
}