AirLetters: An Open Video Dataset of Characters Drawn in the Air
<|reference_start|>AirLetters: An Open Video Dataset of Characters Drawn in the Air: We introduce AirLetters, a new video dataset consisting of real-world videos of human-generated, articulated motions. Specifically, our dataset requires a vision model to predict letters that humans draw in the air. Unlike existing video datasets, accurate classification predictions for AirLetters rely critically on discerning motion patterns and on integrating long-range information in the video over time. An extensive evaluation of state-of-the-art image and video understanding models on AirLetters shows that these methods perform poorly and fall far behind a human baseline. Our work shows that, despite recent progress in end-to-end video understanding, accurate representations of complex articulated motions -- a task that is trivial for humans -- remains an open problem for end-to-end learning.<|reference_end|>
@article{dagli2024airletters:,
    title={AirLetters: An Open Video Dataset of Characters Drawn in the Air},
    author={Rishit Dagli and Guillaume Berger and Joanna Materzynska and Ingo Bax
  and Roland Memisevic},
    journal={arXiv preprint arXiv:2410.02921},
    year={2024},
    archivePrefix={arXiv},
    eprint={2410.02921},
    primaryClass={cs.CV}
}