Social networking based on asset items

A system, comprising:

• at least one processor;
• and
• at least one memory communicatively coupled to the at least one processor and comprising computer-readable instructions that upon execution by the at least one processor cause the at least one processor to perform operations comprising:
• extracting features from an image comprising an object using a first deep learning network model, wherein the object is associated with a location, and wherein the first deep learning network model is configured to be installed on a client computing device associated with a first user;
• determining, by the client computing device, a plurality of pre-stored files based on the location, wherein the plurality of pre-stored files corresponds to a plurality of objects proximate to the location, and each of the plurality of pre-stored files comprises data indicative of a corresponding object from the plurality of objects, wherein each of the plurality of pre-stored files comprises features extracted from one or more images comprising the corresponding object, and the features are extracted from the one or more images using a second deep learning network model;
• recognizing, by the client computing device, the object based on comparing the features extracted from the image with data comprised in each of the plurality of pre-stored files;
• receiving an asset item in response to recognizing the object;
• displaying a video stream via an interface of the client computing device, wherein the video stream comprises a second user;
• rendering an image of the asset item onto the second user in the video stream;
• and
• displaying at least one selectable user interface element via the interface of the client computing device in response to the second user requesting to trade at least one different asset item associated with the second user for the asset item, wherein the at least one selectable user interface element is selectable by the first user to confirm or deny the requested trade.

A non-transitory computer-readable storage medium, storing computer-readable instructions that upon execution by a processor cause the processor to implement operations comprising:

• extracting features from an image comprising an object using a first deep learning network model, wherein the object is associated with a location, and wherein the first deep learning network model is configured to be installed on a client computing device associated with a first user;
• determining, by the client computing device, a plurality of pre-stored files based on the location, wherein the plurality of pre-stored files corresponds to a plurality of objects proximate to the location, and each of the plurality of pre-stored files comprises data indicative of a corresponding object from the plurality of objects, wherein each of the plurality of pre-stored files comprises features extracted from one or more images comprising the corresponding object, and the features are extracted from the one or more images using a second deep learning network model;
• recognizing, by the client computing device, the object based on comparing the features extracted from the image with data comprised in each of the plurality of pre-stored files;
• receiving an asset item in response to recognizing the object;
• displaying a video stream via an interface of the client computing device, wherein the video stream comprises a second user;
• rendering an image of the asset item onto the second user in the video stream;
• and
• displaying at least one selectable user interface element via the interface of the client computing device in response to the second user requesting to trade at least one different asset item associated with the second user for the asset item, wherein the at least one selectable user interface element is selectable by the first user to confirm or deny the requested trade.