Amazon Technologies, Inc.

Qipin Chen

Lingyun Wang

Jack Patrick Copeland

Han Li

Ning Xie

Xing Ju

Yuan Chen

Gordon Snow Zhang

Devices, systems, and methods are provided for smart shopping based on recognition of objects presented in video. A method may include identifying, by a first device, using a machine learning model using a computer vision technique, objects represented in video content; determining that an object of the objects is available for purchase using an online retail system; causing concurrent presentation of the video content and a first indication that the object is available for purchase using the online retail system; receiving, from a second device, a second indication of a user selection of the first indication, wherein the user selection is indicative of a request to present additional information associated with the object; generating, based on the request, presentation data including the additional information and an option to purchase the object using the online retail system; and causing, based on the request, presentation of the presentation data.

Enhanced shopping based on recognition of objects presented in video

Techniques for performing a machine learning model based spatial-temporal adaptive shift for end-to-end text-video retrieval are described. According to some examples, a computer-implemented method includes receiving a video comprising a plurality of frames at a content delivery service; generating, by the content delivery service, a set of embeddings for each of a plurality of sections of each frame of the plurality of frames; determining, by a candidate selector machine learning model of the content delivery service, a proper subset of the plurality of sections of each frame of the plurality of frames for a time shift based on the set of embeddings; time shifting, by the content delivery service, the proper subset of the plurality of sections of each frame of the plurality of frames to generate time shifted frames; generating, by the content delivery service, an updated set of embeddings based on the time shifted frames; receiving a search request comprising input text from a user device; determining the video is a match for the search request based on the input text and the updated set of embeddings for the time shifted frames; and sending the video to the user device based on the match.

Computer-implemented methods for machine learning model based spatial-temporal adaptive shift for end-to-end text-video retrieval

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Bellevue, WA, United States of America

Qipin Chen