Amazon Technologies, Inc.

Michael Lawrence LeKander

Sheng Chen

Hamed Pirsiavash

Ayan Tuhinendu Sinha

Mark Buckler

Hitesh Arora

Todd Hester

Techniques are generally described for fusing sensor data of different modalities using a transformer. In various examples, first sensor data may be received from a first sensor and second sensor data may be received from a second sensor. A first feature representation of the first sensor data may be generated using a first machine learning model and a second feature representation of the second sensor data may be generated using a second machine learning model. In some examples, a modified first feature representation of the first sensor data may be generated based at least in part on a self-attention mechanism of a transformer encoder. The modified first feature representation may be generated based at least in part on the first feature representation and the second feature representation. A computer vision task may be performed using the modified first feature representation.

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Seattle, WA, United States of America

Michael Lawrence LeKander