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It's Time for Artistic Correspondence in Music and Video
In order to capture the high-level concepts that are required to solve the task, we propose modeling the long-term temporal context of both the video and the music signals, using Transformer networks for each modality.
Revealing Occlusions with 4D Neural Fields
For computer vision systems to operate in dynamic situations, they need to be able to represent and reason about object permanence.
Learning Words by Drawing Images
Our goal is to learn the correspondence between spoken words and abstract visual attributes, from a dataset of spoken descriptions of images.
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