A platform for design of a lighting installation generally includes an automated search engine for retrieving and storing a plurality of lighting objects in a lighting object library and a lighting design environment providing a visual representation of a lighting space containing lighting space objects and lighting objects. The visual representation is based on properties of the lighting space objects and lighting objects obtained from the lighting object library. A plurality of aesthetic filters is configured to permit a designer in a design environment to adjust parameters of the plurality of lighting objects handled in the design environment to provide a desired collective lighting effect using the plurality of lighting objects.

Systems, methods, and computer readable media for customizable avatar generation system, where the methods include accessing text data, processing, using at least one processor, the text data to determine first characteristics of the text data, selecting a personalized avatar of a plurality of personalized avatars for the text data based on matching the first characteristics with second characteristics of the plurality of personalized avatars, generating a customized avatar based on the text data and the selected personalized avatar, and causing the customized avatar to be displayed on a display of a computing device.

Methods and systems described herein are directed to creating an artificial reality environment having elements automatically created from source images. In response to a creation system receiving the source images, the system can employ a multi-layered comparative analysis to obtain virtual object representations of objects depicted in the source images. A first set of the virtual objects can be selected from a library by matching identifiers for the depicted objects with tags on virtual objects in the library. A second set of virtual objects can be objects for which no candidate first virtual objects was adequately matched in the library, prompting the creation of a virtual object by generating depth data and skinning a resulting 3D mesh based on the source images. Having determined the virtual objects, the system can compile them into the artificial reality environment according to relative locations determined from the source images.

A method of generating an augmented reality lens comprises: causing to display a list of lens categories on a display screen of a client device; receiving a user choice from the displayed list; causing to prepopulate a lens features display on the display device based on the user choice, wherein each lens feature comprises image transformation data configured to modify or overlay video or image data; receiving a user selection of a lens feature from the prepopulated lens display; receiving a trigger selection that activates the lens feature to complete the lens; and saving the completed lens to a memory of a computer device.

A system for positioning objects within an environment includes: an input unit operable to receive data representative of at least a portion of an environment comprising one or more features associated with the environment; an object determining unit operable to identify, for one or more objects, one or more features associated with each respective object, and operable to determine which of the one or more objects are to be positioned within the environment; and an object positioning unit operable to position the one or more determined objects within the environment in dependence upon at least one of the features associated with the environment and at least one of the features associated with each respective determined object, where the object positioning unit is operable to utilise a machine learning model, trained using one or more examples of one or more other objects positioned within at least a portion of one or more other environments in dependence upon at least one feature associated with each respective other environment and at least one feature associated with each respective other object as an input, to position the one or more determined objects within the environment.

Methods, systems, and non-transitory computer readable storage media are disclosed for utilizing a visual neural network to replace materials in a three-dimensional scene with visually similar materials from a source dataset. Specifically, the disclosed system utilizes the visual neural network to generate source deep visual features representing source texture maps from materials in a plurality of source materials. Additionally, the disclosed system utilizes the visual neural network to generate deep visual features representing texture maps from materials in a digital scene. The disclosed system then determines source texture maps that are visually similar to the texture maps of the digital scene based on visual similarity metrics that compare the source deep visual features and the deep visual features. Additionally, the disclosed system modifies the digital scene by replacing one or more of the texture maps in the digital scene with the visually similar source texture maps.

Techniques and systems are described to render digital images on a defined substrate. In an example, a three-dimensional model is generated of the digital image as disposed on a substrate. Generation of the model includes application of a three-dimensional model of a surface of the substrate to the digital image and addition of material properties of the substrate to the three-dimensional model of the digital image). A viewing direction is detected of the three-dimensional model of the digital image, the detecting based on one or more sensors of the computing device. An effect of light is also ascertained on the three-dimensional model of the digital image having the material properties of the substrate at the detected viewing direction. The three-dimensional model of the digital image is rendered based on the detected viewing direction and the ascertained effect of light for display by the computing device.

An image processing method is provided. The method includes generating appearance information corresponding to a canonical space defined by a cube including a plurality of regular grids in a first input image by implementing a first neural network, generating geometric information corresponding to a standard space in a second input image by implementing a second neural network, deforming the plurality of regular grids based on the generated geometric information, generating standardized image information by applying the appearance information to the plurality of deformed regular grids, and generating an output image based on the standardized image information.

In one example, a method performed by a processing system including at least one processor includes identifying a background for a scene of video content, generating a three-dimensional model and visual effects for an object appearing in the background for the scene of video content, displaying a three-dimensional simulation of the background for the scene of video content, including the three-dimensional model and visual effects for the object, modifying the three-dimensional simulation of the background for the scene of video content based on user feedback, capturing video footage of a live action subject appearing together with the background for the scene of video content, where the live action subject appearing together with the background for the scene of video content creates the scene of video content, and saving the scene of video content.

A computer-implemented method for duplicating a GUI element in a 3D scene including obtaining a 3D model and GUI element displayed in the 3D scene, the GUI element including an anchor attached to the 3D model and including a body being window containing text and/or graphical elements, receiving a first user interaction indicative of a hold gesture on the anchor, by a user using a first appendage, while maintaining the hold gesture of the first appendage on the anchor, receiving a second user interaction indicative a hold gesture on the body, by the user using a second appendage, while maintaining the hold gesture using the first and second appendage, moving the second appendage outside the body, thereby duplicating the GUI element into a second GUI element, including an anchor, the position of the anchor of the second GUI element being defined by the position of second appendage.