Google Inc.

Anurag Arnab

Mostafa Dehghani

Cordelia Luise Schmid

Anelia Angelova

Chen Sun

Anthony Jacob Piergiovanni

Georg Heigold

Michael Sahngwon Ryoo

Mario Lucic

Arsha Nagrani

Hongsuck Seo

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing a network input using a computer vision neural network with learned tokenization.

Computer vision neural networks with learned tokenization

Systems and methods method for performing captioning for image or video data are described herein. The method can include receiving unlabeled multimedia data, and outputting, from a machine learning model, one or more captions for the multimedia data. Training the machine learning model to create these outputs can include inputting a subset of video frames and a first utterance into the machine learning model, using the machine learning model to predict a predicted utterance based on the subset of video frames and the first utterance, and updating one or more parameters of the machine learning model based on a loss function that compares the predicted utterance with the second utterance.

Pre-training a model using unlabeled videos

A computer-implemented method for classifying video data with improved accuracy includes obtaining, by a computing system comprising one or more computing devices, video data comprising a plurality of video frames; extracting, by the computing system, a plurality of video tokens from the video data, the plurality of video tokens comprising a representation of spatiotemporal information in the video data; providing, by the computing system, the plurality of video tokens as input to a video understanding model, the video understanding model comprising a video transformer encoder model; and receiving, by the computing system, a classification output from the video understanding model.

Systems and methods for improved video understanding

Growing community of inventors

Grenoble, France

Anurag Arnab