Abstract: In some examples, a computing system accesses a field of view (FOV) image that has a field of view less than 360 degrees and has low dynamic range (LDR) values. The computing system estimates lighting parameters from a scene depicted in the FOV image and generates a lighting image based on the lighting parameters. The computing system further generates lighting features generated the lighting image and image features generated from the FOV image. These features are aggregated into aggregated features and a machine learning model is applied to the image features and the aggregated features to generate a panorama image having high dynamic range (HDR) values.

Abstract: A scene modeling system receives a plurality of input two-dimensional (2D) images corresponding to a plurality of views of an object and a request to display a three-dimensional (3D) scene that includes the object. The scene modeling system generates an output 2D image for a view of the 3D scene by applying a scene representation model to the input 2D images. The scene representation model includes a point cloud generation model configured to generate, based on the input 2D images, a neural point cloud representing the 3D scene. The scene representation model includes a neural point volume rendering model configured to determine, for each pixel of the output image and using the neural point cloud and a volume rendering process, a color value. The scene modeling system transmits, responsive to the request, the output 2D image. Each pixel of the output image includes the respective determined color value.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media that generate three-dimensional hybrid mesh-volumetric representations for digital objects. For instance, in one or more embodiments, the disclosed systems generate a mesh for a digital object from a plurality of digital images that portray the digital object using a multi-view stereo model. Additionally, the disclosed systems determine a set of sample points for a thin volume around the mesh. Using a neural network, the disclosed systems further generate a three-dimensional hybrid mesh-volumetric representation for the digital object utilizing the set of sample points for the thin volume and the mesh.

Abstract: A method for providing a relightable avatar of a subject to a virtual reality application is provided. The method includes retrieving multiple images including multiple views of a subject and generating an expression-dependent texture map and a view-dependent texture map for the subject, based on the images. The method also includes generating, based on the expression-dependent texture map and the view-dependent texture map, a view of the subject illuminated by a light source selected from an environment in an immersive reality application, and providing the view of the subject to an immersive reality application running in a client device. A non-transitory, computer-readable medium storing instructions and a system that executes the instructions to perform the above method are also provided.

Abstract: A method for providing a relightable avatar of a subject to a virtual reality application is provided. The method includes retrieving multiple images including multiple views of a subject and generating an expression-dependent texture map and a view-dependent texture map for the subject, based on the images. The method also includes generating, based on the expression-dependent texture map and the view-dependent texture map, a view of the subject illuminated by a light source selected from an environment in an immersive reality application, and providing the view of the subject to an immersive reality application running in a client device. A non-transitory, computer-readable medium storing instructions and a system that executes the instructions to perform the above method are also provided.

Abstract: Enhanced methods and systems for generating both a geometry model and an optical-reflectance model (an object reconstruction model) for a physical object, based on a sparse set of images of the object under a sparse set of viewpoints. The geometry model is a mesh model that includes a set of vertices representing the object's surface. The reflectance model is SVBRDF that is parameterized via multiple channels (e.g., diffuse albedo, surface-roughness, specular albedo, and surface-normals). For each vertex of the geometry model, the reflectance model includes a value for each of the multiple channels. The object reconstruction model is employed to render graphical representations of a virtualized object (a VO based on the physical object) within a computation-based (e.g., a virtual or immersive) environment. Via the reconstruction model, the VO may be rendered from arbitrary viewpoints and under arbitrary lighting conditions.

Abstract: Enhanced methods and systems for generating both a geometry model and an optical-reflectance model (an object reconstruction model) for a physical object, based on a sparse set of images of the object under a sparse set of viewpoints. The geometry model is a mesh model that includes a set of vertices representing the object's surface. The reflectance model is SVBRDF that is parameterized via multiple channels (e.g., diffuse albedo, surface-roughness, specular albedo, and surface-normals). For each vertex of the geometry model, the reflectance model includes a value for each of the multiple channels. The object reconstruction model is employed to render graphical representations of a virtualized object (a VO based on the physical object) within a computation-based (e.g., a virtual or immersive) environment. Via the reconstruction model, the VO may be rendered from arbitrary viewpoints and under arbitrary lighting conditions.

Abstract: A scene reconstruction system renders images of a scene with high-quality geometry and appearance and supports view synthesis, relighting, and scene editing. Given a set of input images of a scene, the scene reconstruction system trains a network to learn a volume representation of the scene that includes separate geometry and reflectance parameters. Using the volume representation, the scene reconstruction system can render images of the scene under arbitrary viewing (view synthesis) and lighting (relighting) locations. Additionally, the scene reconstruction system can render images that change the reflectance of objects in the scene (scene editing).

Abstract: A method for providing a relightable avatar of a subject to a virtual reality application is provided. The method includes retrieving multiple images including multiple views of a subject and generating an expression-dependent texture map and a view-dependent texture map for the subject, based on the images. The method also includes generating, based on the expression-dependent texture map and the view-dependent texture map, a view of the subject illuminated by a light source selected from an environment in an immersive reality application, and providing the view of the subject to an immersive reality application running in a client device. A non-transitory, computer-readable medium storing instructions and a system that executes the instructions to perform the above method are also provided.