Snap Inc.

Peleg Harel

Gal Dudovitch

Itamar Berger

Ma'ayan Mishin Shuvi

Avihay Assouline

Gal Sasson

Sergei Korolev

Chia-Hao Hsieh

Matan Zohar

Nir Malbin

Methods and systems are disclosed for generating mirrored 3D assets for an extended reality (XR) experience. The system receives a three-dimensional (3D) object comprising a target and analyzes the 3D object using one or more machine learning models to generate data associated with a mirrored version of the target of the 3D object. The system applies the mirrored version of the target to a mirrored version of the 3D object using the generated data and generates a new 3D object comprising the mirrored version of the 3D object and the mirrored version of the target.

Mirroring 3D assets for virtual experiences

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 a video that includes a depiction of a real-world object in a real-world environment; determining a classification for the real-world environment by processing the real-world object depicted in the video; selecting an augmented reality (AR) item based on the classification of the real-world environment and the real-world object depicted in the video; modifying pixels corresponding to the real-world object depicted in the video to generate a modified video that excludes the depiction of the real-world object; and adding the AR item to the modified video at a display position corresponding to the modified pixels.

Method, system, and medium for augmented reality product recommendations

Aspects of the present disclosure involve a system for presenting AR items. The system performs operations including receiving a video that includes a depiction of one or more real-world objects in a real-world environment and obtaining depth data related to the real-world environment. The operations include generating a three-dimensional (3D) model of the real-world environment based on the video and the depth data and adding an augmented reality (AR) item to the video based on the 3D model of the real-world environment. The operations include determining that the AR item has been placed on a vertical plane of the real-world environment and modifying an orientation of the AR item to correspond to an orientation of the vertical plane.

AR position and orientation along a plane

Methods and systems are disclosed for performing operations comprising: receiving a monocular image that includes a depiction of a whole body of a user; generating a segmentation of the whole body of the user based on the monocular image; accessing a video feed comprising a plurality of monocular images received prior to the monocular image; smoothing, using the video feed, the segmentation of the whole body generated based on the monocular image to provide a smoothed segmentation; and applying one or more visual effects to the monocular image based on the smoothed segmentation.

Whole body segmentation

Aspects of the present disclosure involve a system for presenting AR items. The system receives a video that includes a depiction of a real-world object in a real-world environment. The system generates a three-dimensional (3D) bounding box for the real-world object and stabilizes the 3D bounding box based on one or more sensors of the device. The system determines a position, orientation, and dimensions of the real-world object based on the stabilized 3D bounding box and renders a display of an augmented reality (AR) item within the video based on the position, orientation, and dimensions of the real-world object.

9-DoF object tracking

Aspects of the present disclosure involve a system for performing real-time in-painting using machine learning techniques. The system receives a video that includes a depiction of a real-world object in a real-world environment. The system accesses a segmentation associated with the real-world object and removes a depiction of the real-world object from a region of a first frame of the video. The system processes, by a machine learning model, the first frame and one or more previous frames of the video that precede the first frame to generate a new frame in which portions of the first frame have been blended into the region from which the depiction of the real-world object has been removed.

Real-time machine learning based in-painting

Methods and systems are disclosed for performing operations comprising: receiving a monocular image that includes a depiction of a whole body of a user; generating a segmentation of the whole body of the user based on the monocular image by applying one or more machine learning techniques; receiving input that selects a visualization mode; and applying one or more visual effects corresponding to the visualization mode to the monocular image based on the segmentation.

Whole body visual effects

Methods and systems are disclosed for performing operations comprising: receiving a monocular image that includes a depiction of a user wearing a garment; generating a segmentation of the garment worn by the user in the monocular image; accessing a video feed comprising a plurality of monocular images received prior to the monocular image; smoothing, using the video feed, the segmentation of the garment worn by the user to provide a smoothed segmentation of the garment worn by the user; and applying one or more visual effects to the monocular image based on the smoothed segmentation of the garment worn by the user.

Garment segmentation

Aspects of the present disclosure involve a system for providing AR experiences. The system accesses, by a messaging application, an image depicting a real-world fashion item of a user and generates a three-dimensional (3D) virtual fashion item based on the real-world fashion item depicted in the image. The system stores the 3D virtual fashion item in a database that includes a virtual wardrobe comprising a plurality of 3D virtual fashion items associated with the user. The system generates, by the messaging application, an augmented reality (AR) experience that allows the user to interact with the virtual wardrobe.

Virtual wardrobe AR experience

Aspects of the present disclosure involve a system for providing virtual experiences. The system performs operations including selecting, by a messaging application, a virtual experience that represents a previously captured real-world environment at a first location; accessing an image representing a new real-world environment at a second location, the image depicting a plurality of real-world objects; receiving input that selects a first real-world object from the plurality of real-world objects depicted in the image; and modifying the image, accessed at the second location, based on the virtual experience to depict the previously captured real-world environment with the first real-world object.

Applying pregenerated virtual experiences in new location

Aspects of the present disclosure involve a system for presenting augmented reality (AR) items. The system performs operations including receiving a video that includes a depiction of a real-world environment and generating a 3D model of the real-world environment based on the video. The operations include determining, based on the 3D model of the real-world environment, that an AR item has been placed in the video at a particular 3D position and identifying a portion of the 3D model corresponding to the real-world environment currently being displayed on a screen. The operations include determining that the 3D position of the AR item is excluded from the portion of the 3D model currently being displayed on the screen and in response, displaying an indicator that identifies the 3D position of the AR item in the 3D model relative to the portion of the 3D model currently being displayed on a screen.

Growing community of inventors

Ramat Gan, Israel

Peleg Harel