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We introduce PyTorchVideo, an open-source deep-learning library that provides a rich set of modular, efficient, and reproducible components for a variety of video understanding tasks, including classification, detection, self-supervised learning, and low-level processing. The library covers a full stack of video understanding tools including multimodal data loading, transformations, and models that reproduce state-of-the-art performance. PyTorchVideo further supports hardware acceleration that enables real-time inference on mobile devices. The library is based on PyTorch and can be used by any training framework; for example, PyTorchLightning, PySlowFast, or Classy Vision. PyTorchVideo is available at https://pytorchvideo.org/.
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Haoqi Fan
Beijing University of Technology
Tullie Murrell
Menlo School
Heng Wang
Shanghai Maritime University
Menlo School
Meta (United States)
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Fan et al. (Sun,) studied this question.
synapsesocial.com/papers/6a1a4b97aa5cc20a989bb0a4 — DOI: https://doi.org/10.1145/3474085.3478329
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