公开(公告)号：US20250044912A1

公开(公告)日：2025-02-06

申请号：US18790543

申请日：2024-07-31

Applicant: Snap Inc.

Inventor： Shubham Chawla ,  Hyojung Chun ,  Anvi Dalal ,  Yunchu He ,  Hao Hu ,  Sarah Lensing ,  Yanjia Li ,  Ana Medinac ,  Bindi Patel ,  Patrick Poirson ,  Chiung-Fu Shih ,  Jeremy Staub ,  Kevin Dechau Tang ,  Ryan Tran ,  Andrew Wan ,  Cindy Wang ,  Alireza Zareian

IPC: G06F3/04817 ,  G06V10/764

Abstract: Systems and methods for object-based content recommendation are described. A camera feed comprising a plurality of image frames is caused to be displayed at a client device. An object is detected within an image frame from the camera feed, the object corresponding with an object category. Responsive to detecting the object, an icon associated with the object category is selected and displayed at a position upon the camera feed. The icon corresponds with a media collection related to the object category. An input is received selecting the icon. Responsive to the input, a presentation of media items from the media collection is displayed at the client device. By detecting real-world objects and surfacing relevant virtual icons that link to associated media, an augmented reality experience is provided allowing virtual content to be overlaid and anchored to objects in reality.

公开(公告)号：US20240355063A1

公开(公告)日：2024-10-24

申请号：US18304078

申请日：2023-04-20

Applicant: Snap Inc.

Inventor： Zhenpeng Zhou ,  Patrick Poirson ,  Maksim Gusarov ,  Chen Wang ,  Oleg Tovstyi

IPC: G06T19/00 ,  G06T1/00 ,  G06V10/74 ,  H04N5/262

CPC classification number: G06T19/006 ,  G06T1/0021 ,  G06V10/761 ,  H04N5/2621

Abstract: An input video item that includes a target visual augmentation is accessed. A machine learning model uses the input video item to generate an embedding. The embedding may comprise a vector representation of a visual effect of the target visual augmentation. The machine learning model is trained, in an unsupervised training phase, to minimize loss between training video representations generated within each of a plurality of training sets. Each training set comprises a plurality of different training video items that each include a predefined visual augmentation. Based on the generation of the embedding of the input video item, the target visual augmentation is mapped to an augmentation identifier.

公开(公告)号：US12254049B2

公开(公告)日：2025-03-18

申请号：US18054420

申请日：2022-11-10

Applicant: Snap Inc.

Inventor： Kevin Sarabia Dela Rosa ,  Adel Elmalaha ,  Kwot Sin Lee ,  Patrick Poirson

IPC: G06F16/83 ,  G06F16/903 ,  G06F16/9035 ,  G06F16/907 ,  G06T19/00 ,  G06V10/74

Abstract: Aspects of the present disclosure involve a system comprising a computer-readable storage medium storing a program and a method for performing operations comprising: receiving an image from a client device; applying a machine learning model to the image to generate an embedding query vector, the machine learning model being trained to encode a plurality of images and text into a common embedding space; searching, based on the embedding query vector, a database of augmented reality (AR) experiences to identify a subset of AR experiences associated with one or more embeddings that correspond to the embedding query vector; and transmitting to the client device the subset of AR experiences associated with the one or more embeddings that correspond to the embedding query vector.

公开(公告)号：US20240160673A1

公开(公告)日：2024-05-16

申请号：US18054420

申请日：2022-11-10

Applicant: Snap Inc.

Inventor： Kevin Sarabia Dela Rosa ,  Adel Elmalaha ,  Kwot Sin Lee ,  Patrick Poirson

IPC: G06F16/907 ,  G06F16/903 ,  G06F16/9035 ,  G06T19/00 ,  G06V10/74

CPC classification number: G06F16/907 ,  G06F16/90335 ,  G06F16/9035 ,  G06T19/006 ,  G06V10/761

Abstract: Aspects of the present disclosure involve a system comprising a computer-readable storage medium storing a program and a method for performing operations comprising: receiving an image from a client device; applying a machine learning model to the image to generate an embedding query vector, the machine learning model being trained to encode a plurality of images and text into a common embedding space; searching, based on the embedding query vector, a database of augmented reality (AR) experiences to identify a subset of AR experiences associated with one or more embeddings that correspond to the embedding query vector; and transmitting to the client device the subset of AR experiences associated with the one or more embeddings that correspond to the embedding query vector.