Yahoo Assets LLC

Oath Inc.

Verizon Patent and Licensing Inc.

Joao Vitor Baldini Soares

Yale Song

Guy Dassa

Jeffrey Scholz

Minho Lee

Simao Herdade

Kofi Boakye

Armin Kappeler

Paloma De Juan

In some implementations, the techniques described herein relate to a method including: (i) receiving, by a processor that executes a digital messaging application, an image that comprises a depiction of a user, (ii) selecting, by the processor, an event theme, (iii) creating, by a generative machine learning model, a generated image that comprises the depiction of the user and the event theme, and (iv) transmitting, by the processor, the generated image to one or more digital contacts of the user via the digital messaging application.

Systems and methods for programmatically generating custom greeting cards

Disclosed are systems and methods for improving interactions with and between computers in content hosting and/or providing systems supported by or configured with personal computing devices, servers and/or platforms. The systems interact to identify and retrieve data within or across platforms, which can be used to improve the quality of data used in processing interactions between or among processors in such systems. The disclosed systems and methods provide systems and methods for automatically creating a caption comprising a sequence of words in connection with digital content.

Automatic digital content captioning using spatial relationships method and apparatus

Disclosed are systems and methods for improving interactions with and between computers in content searching, hosting and/or providing systems supported by or configured with devices, servers and/or platforms. The disclosed systems and methods provide an image processing framework that sub-divides computer vision techniques into three computationally efficient steps: detection, classification and matching. These steps provide an improved image processing framework that can analyze live stream data of a media file, in real-time, in order to identify and track specific digital objects depicted therein. This enables not only image processing detection results, but also the capabilities of augmenting the video stream with additional data related to the detected object.

Computer vision on broadcast video

Disclosed are systems and methods for improving interactions with and between computers in content searching, hosting and/or providing systems supported by or configured with devices, servers and/or platforms. The disclosed systems and methods provide a novel machine-in-the-loop, image-to-video bootstrapping framework that harnesses a training set built upon an image dataset and a video dataset in order to efficiently produce an accurate training set to be applied to frames of videos. The disclosed systems and methods reduce the amount of time required to build the training dataset, and also provide mechanisms to apply the training dataset to any type of content and for any type of recognition task.

Machine-in-the-loop, image-to-video computer vision bootstrapping

Growing community of inventors

New York, NY, United States of America

Joao Vitor Baldini Soares