Snap Inc.

Harsh Agrawal

Xuan Huang

Yuncheng Li

William Brendel

Xiaoyu Wang

Yiwei Ma

Ye Tao

Meng Song

Tao Ning

Jung Hyun Kim

Systems, methods, devices, computer readable instruction media, and other embodiments are described for automated image processing and insight presentation. One embodiment involves receiving a plurality of ephemeral content messages from a plurality of client devices, and processing the messages to identify content associated with at least a first content type. A set of analysis data associated with the first content type is then generated from the messages, and portions of the messages associated with the first content type are processed to generate a first content collection. The first content collection and the set of analysis data are then communicated to a client device configured for a display interface comprising the first content collection and a representation of at least a portion of the set of analysis data.

Automated image processing and insight presentation

Systems, devices, media, and methods are presented for graphical icon identification within an image or video stream. The systems and methods receive an image including a graphical icon. The systems and methods identify a set of proposed regions of the image, at least one proposed region of the set of proposed regions containing the graphical icon and extract a set of semantic features for each proposed region of the set of proposed regions. Based on the set of semantic features of the set of proposed regions, the systems and methods identify a set of proposed icons corresponding to the graphical icon included in the image and determine a match between the graphical icon and at least one proposed icon of the set of proposed icons.

Machine learned single image icon identification

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Atlanta, GA, United States of America

Harsh Agrawal