Qualcomm Incorporated

Qualcomm Technologies, Inc.

Deepak Kumar Gupta

Efstratios Gavves

Arnold Wilhelmus Maria Smeulders

Christen Maximilian Filtenborg

A method for object tracking includes receiving a target image of an object of interest. Latent space features of the target image is modified at a forward pass for a neural network by dropping at least one channel of the latent space features, dropping a channel corresponding to a slice of the latent space features, or dropping one or more features of the latent space features. At the forward pass, a location of the object of interest in a search image is predicted based on the modified latent space features. The location of the object of interest is identified by aggregating predicted locations from the forward pass.

Managing occlusion in Siamese tracking using structured dropouts

A computer-implemented method for tracking with visual object constraints includes receiving a lingual constraint and a video. A word embedding is generated based on the lingual constraint. A set of features is extracted for one or more frames of the video. The word embedding is cross-correlated to the set of features for the one or more frames of the video. A prediction indicating whether the lingual constraint is in the one or more frames of the video is generated based on the cross-correlation.

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Amsterdam, Netherlands

Deepak Kumar Gupta