Snap Inc.

Aleksandr Zakharov

Sergey Smetanin

Pavel Savchenkov

Roman Golobokov

Arnab Ghosh

Sofya Savinova

Daniel Moreno

Sergey Tulyakov

Jian Ren

Nikita Demidov

Ivan Babanin

Nikita Belosludtcev

Dor Ayalon

Timur Zakirov

Vladimir Gordienko

Examples disclosed herein describe techniques related to automated image generation in an interaction system. An image generation request is received from a first user device associated with a first user of an interaction system. The image generation request comprises a text prompt. Responsive to receiving the image generation request, an image is automatically generated by an automated text-to-image generator, based on the text prompt. The image is caused to be presented on the first user device. An indication of user input to select the image is received from the user device. Responsive to receiving the indication of the user input to select the image, the image is associated with the first user within the interaction system, and a second user of the interaction system is enabled to be presented with the image.

Automatic image generation in an interaction system

Examples disclosed herein describe prompt modification techniques for automated image generation. An image generation request comprising a base prompt is received from a user device. A plurality of prompt modifiers is identified. A processor-implemented scoring engine determines, for each prompt modifier, a modifier score. The modifier score for each prompt modifier is associated with the base prompt. One or more of the prompt modifiers are automatically selected based on the modifier scores. A modified prompt is generated. The modified prompt is based on the base prompt and the one or more selected prompt modifiers. The modified prompt is provided as input to an automated image generator to generate an image, and the image is caused to be presented on the user device.

Prompt modification for automated image generation

Described herein is a technique for processing a received media content item (e.g., a message), received at a messaging application of a first end-user of a messaging service, to generate a selection of some predetermined number of recommended stickers. The recommended stickers are then presented in a user interface to the first end-user, allowing the first end-user to select a sticker for use in replying to the received media content item. To generate the selection of recommended stickers, in response to receiving the media content item, the messaging application processes the media content item to identify specific attributes and characteristics (e.g., text included with the message, stickers used with the message, and other contextual metadata). The identified attributes and characteristics of the received message are then processed by a scoring model to identify the predetermined number of stickers for presenting in the reply interface as recommended reply stickers.

Techniques for recommending reply stickers

Growing community of inventors

Dubai, United Arab Emirates

Aleksandr Zakharov