Contains 50 minutes of footage with both color frames and events. CED features a wide variety of indoor and outdoor scenes.
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The N-ImageNet dataset is an event-camera counterpart for the ImageNet dataset. The dataset is obtained by moving an event camera around a monitor displaying images from ImageNet. N-ImageNet contains approximately 1,300k training samples and 50k validation samples. In addition, the dataset also contains variants of the validation dataset recorded under a wide range of lighting or camera trajectories. Additional details about the dataset are explained in the paper available through this link. Please cite this paper if you make use of the dataset.
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TUM-VIE is an event camera dataset for developing 3D perception and navigation algorithms. It contains handheld and head-mounted sequences in indoor and outdoor environments with rapid motion during sports and high dynamic range. TUM-VIE includes challenging sequences where state-of-the art VIO fails or results in large drift. Hence, it can help to push the boundary on event-based visual-inertial algorithms.
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Event-Human3.6m is a challenging dataset for event-based human pose estimation by simulating events from the RGB Human3.6m dataset. It is built by converting the RGB recordings of Human3.6m into events and synchronising raw joints ground-truth with events frames through interpolation.
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