This task offers researchers an opportunity to test their fine-grained classification methods for detecting and recognizing strokes in table tennis videos. (The low inter-class variability makes the task more difficult than with usual general datasets like UCF-101.) The task offers two subtasks:
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InfiniteRep is a synthetic, open-source dataset for fitness and physical therapy (PT) applications. It includes 1k videos of diverse avatars performing multiple repetitions of common exercises. It includes significant variation in the environment, lighting conditions, avatar demographics, and movement trajectories. From cadence to kinematic trajectory, each rep is done slightly differently -- just like real humans. InfiniteRep videos are accompanied by a rich set of pixel-perfect labels and annotations, including frame-specific repetition counts.
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