Omnivore: A Single Model for Many Visual Modalities. (arXiv:2201.08377v1 [cs.CV])

Prior work has studied different visual modalities in isolation and developed
separate architectures for recognition of images, videos, and 3D data. Instead,
in this paper, we propose a single model which excels at classifying images,
videos, and single-view 3D data using exactly the same model parameters. Our
'Omnivore' model leverages the flexibility of transformer-based architectures
and is trained jointly on classification tasks from different modalities.
Omnivore is simple to train, uses off-the-shelf standard datasets, and performs
at-par or better than …

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