Abstract: Methods and systems are provided for rendering photo-realistic images of a subject or an object using a differentiable neural network for predicting indirect light behavior. In one example, the differentiable neural network outputs a volumetric light map comprising a plurality of spherical harmonic representations. Further, using a reflectance neural network, roughness and scattering coefficients associated with the subject or the object is computed. The volumetric light map, as well as the roughness and scattering coefficients are the utilized for rendering a final image under one or more of a desired lighting condition, desired camera view angle, and/or with a desired visual effect (e.g., expression change).

Abstract: Methods, mediums, and systems for constructing a 3D face model, including Deep Iterative Face Fitting (DIFF) and Recurrent Feature Alignment (ReFA). A processor provides a reference—containing a 3D mesh representing a median face, vertex positions, or surface points—as a template and UV texture mapping pointing the 3D mesh to a 2D UV space; receives input image(s) of a face and extracts geometry/texture features in an image space; extracts features in a UV space; iteratively produces a feature map via visual semantic correlation between UV and image spaces and regress geometry updates, predicting texture maps and comparing features, and inputs the map to an RNN-based neural optimizer of Gated Recurrent Units (GRU) to determine a hidden state. A head pose and/or updated 3D mesh/UV-space position map is output, each pixel in the UV-space map storing a coordinate of a corresponding point in a canonical space of the 3D mesh.

Abstract: A control method, device, apparatus and storage medium for a supercapacitor energy storage device is provided, where the method includes: collecting life characterization parameters of the supercapacitor energy storage device and performing life evaluation to obtain a life evaluation result, inputting the life evaluation result into a constructed fuzzy rule base, and outputting a constraint condition adjustment parameter; obtaining a constraint condition according to the constraint condition adjustment parameter, and optimizing control parameters using a genetic algorithm in conjunction with an optimized objective function to obtain first control parameters; and controlling charging and discharging currents of the supercapacitor energy storage device using a droop control method according to the first control parameters.

Abstract: Systems and methods are provided for generating topologically consistent meshes across various subjects, objects, and/or various facial expressions using a volumetric representation. In one example, a progressive mesh generation network is configured to embed the topological structure of a subject or an object in a feature volume sampled from a geometry-aware local features. Further, a coarse-to-fine iterative architecture facilitates dense and accurate facial mesh predictions using a consistent mesh topology. In another example, one or more high-quality asset maps may be generated from a final base mesh.

Abstract: Methods and systems are provided for rendering photo-realistic images of a subject or an object using a differentiable neural network for predicting indirect light behavior. In one example, the differentiable neural network outputs a volumetric light map comprising a plurality of spherical harmonic representations. Further, using a reflectance neural network, roughness and scattering coefficients associated with the subject or the object is computed. The volumetric light map, as well as the roughness and scattering coefficients are the utilized for rendering a final image under one or more of a desired lighting condition, desired camera view angle, and/or with a desired visual effect (e.g., expression change).