Abstract: A coated substrate comprising a coating extending over at least a part of the substrate. The coating is obtainable from a coating composition comprising (a) a polymeric binder; and (b) a feathering reducing agent comprising a carboxylic acid reactive functional group. The coated portion of the substrate comprises a pretreatment layer. The pretreatment layer is obtainable from a pretreatment composition that comprises a trivalent chromium compound. The invention extends to a method of coating a pre-treated substrate and a coated package, such as a metal can.

Abstract: A coating composition comprising (a) a polyester binder material; and (b) a feathering reducing agent. The feathering reducing agent is selected from (i) an acrylic feathering reducing agent comprising a functional group selected from hydroxyl, epoxide, phosphatized epoxide and/or acid-functional; (ii) a hydroxy-functional polyester feathering reducing agent; (iii) a feathering reducing agent comprising a functional group selected from amine, amide, imine and/or nitrile; (iv) a phosphatized epoxy feathering reducing agent; (v) a phenolic resin feathering reducing agent; and/or (vi) a feathering reducing agent comprising an oxazolyl functional group. The invention extends to a substrate coated with the coating composition and use of the coating composition to reduce feathering.

Abstract: An image rendering method for rendering a pixel of a virtual scene at a viewpoint includes: downloading a machine learning system corresponding to a current or anticipated state an application determining the virtual scene to be rendered from among a plurality of machine learning systems corresponding to a plurality of states of the application; providing a position and a direction based on the viewpoint to the machine learning system previously trained to predict a factor; combining the predicted factor from the machine learning system with a distribution function that characterises an interaction of light with a predetermined surface to generate the pixel value corresponding to an illuminated first element of the virtual scene at the position; and incorporating the pixel value into a rendered image for display.

Abstract: A modeling engine generates a prediction model that quantifies and predicts secondary dynamics associated with the face of a performer enacting a performance. The modeling engine generates a set of geometric representations that represents the face of the performer enacting different facial expressions under a range of loading conditions. For a given facial expression and specific loading condition, the modeling engine trains a Machine Learning model to predict how soft tissue regions of the face of the performer change in response to external forces applied to the performer during the performance. The modeling engine combines different expression models associated with different facial expressions to generate a prediction model. The prediction model can be used to predict and remove secondary dynamics from a given geometric representation of a performance or to generate and add secondary dynamics to a given geometric representation of a performance.

Abstract: Methods and systems for performing facial retargeting using a patch-based technique are disclosed. One or more three-dimensional (3D) representations of a source character's (e.g., a human actor's) face can be transferred onto one or more corresponding representations of a target character's (e.g., a cartoon character's) face, enabling filmmakers to transfer a performance by a source character to a target character. The source character's 3D facial shape can separated into patches. For each patch, a patch combination (representing that patch as a combination of source reference patches) can be determined. The patch combinations and target reference patches can then be used to create target patches corresponding to the target character. The target patches can be combined using an anatomical local model solver to produce a 3D facial shape corresponding to the target character, effectively transferring a facial performance by the source character to the target character.

Abstract: A system for generating video game inputs is provided. The system comprises an input unit operable to obtain images of a passive non-luminous object being held by a user as a video games controller. The system also comprises an object detector and object pose detector for detecting the object and its respective pose in the obtained images. The pose detector is configured to detect the pose of the object based on at least one of a (i) contour detection operation and (ii) the output of a machine learning model that has been trained to detect the poses of passive non-luminous objects in images. A user input generator is configured to generate user inputs based on the detected changes in pose of the passive non-luminous object and to transmit these to a video game unit at which a video game is being executed. A corresponding method is also provided.

Abstract: A data processing apparatus adapted to output recommendation information for modifying source code, includes: compiler circuitry to compile the source code and to output compiled code for the source code, processing circuitry to execute the compiled code, profile circuitry to monitor the execution of the compiled code by the processing circuitry and to generate profile information for the execution of the compiled code, the profile information including one or more statistical properties for the execution of the compiled code, and recommendation circuitry to output the recommendation information for the source code, the recommendation circuitry including a machine learning model to receive at least a portion of the profile information and trained to output the recommendation information for the source code in dependence upon one or more of the statistical properties, in which the recommendation information is indicative of one or more editing instructions for modifying the source code.

Abstract: Embodiments of the present disclosure are directed to methods and systems for generating three-dimensional (3D) models and facial hair models representative of subjects (e.g., actors or actresses) using facial scanning technology. Methods accord to embodiments may be useful for performing facial capture on subjects with dense facial hair. Initial subject facial data, including facial frames and facial performance frames (e.g., images of the subject collected from a capture system) can be used to accurately predict the structure of the subject’s face underneath their facial hair to produce a reference 3D facial shape of the subject. Likewise, image processing techniques can be used to identify facial hairs and generate a reference facial hair model. The reference 3D facial shape and reference facial hair mode can subsequently be used to generate performance 3D facial shapes and a performance facial hair model corresponding to a performance by the subject (e.g., reciting dialog).

Abstract: One embodiment of the present invention sets forth a technique for performing shape and appearance reconstruction. The technique includes generating a first set of renderings associated with an object based on a set of parameters that represent a reconstruction of the object in a first target image. The technique also includes producing, via a neural network, a first set of corrections associated with at least a portion of the set of parameters based on the first target image and the first set of renderings. The technique further includes generating an updated reconstruction of the object based on the first set of corrections.

Abstract: Methods and systems for performing facial retargeting using a patch-based technique are disclosed. One or more three-dimensional (3D) representations of a source character's (e.g., a human actor's) face can be transferred onto one or more corresponding representations of a target character's (e.g., a cartoon character's) face, enabling filmmakers to transfer a performance by a source character to a target character. The source character's 3D facial shape can separated into patches. For each patch, a patch combination (representing that patch as a combination of source reference patches) can be determined. The patch combinations and target reference patches can then be used to create target patches corresponding to the target character. The target patches can be combined using an anatomical local model solver to produce a 3D facial shape corresponding to the target character, effectively transferring a facial performance by the source character to the target character.

Abstract: Embodiments of the present disclosure are directed to methods and systems for generating three-dimensional (3D) models and facial hair models representative of subjects (e.g., actors or actresses) using facial scanning technology. Methods accord to embodiments may be useful for performing facial capture on subjects with dense facial hair. Initial subject facial data, including facial frames and facial performance frames (e.g., images of the subject collected from a capture system) can be used to accurately predict the structure of the subject's face underneath their facial hair to produce a reference 3D facial shape of the subject. Likewise, image processing techniques can be used to identify facial hairs and generate a reference facial hair model. The reference 3D facial shape and reference facial hair mode can subsequently be used to generate performance 3D facial shapes and a performance facial hair model corresponding to a performance by the subject (e.g., reciting dialog).

Abstract: A data processing apparatus includes input circuitry to receive viewpoint data indicative of respective viewpoints for a plurality of spectators of a virtual environment, detection circuitry to detect a portion of the virtual environment viewed by each of the respective viewpoints in dependence upon the viewpoint data, selection circuitry to select one or more regions of the virtual environment in dependence upon at least some of the detected portions, and output circuitry to output data indicative of one or more of the selected regions.

Abstract: Various embodiments include a system for rendering an object, such as human skin or a human head, from captured appearance data. The system includes a processor executing a near field lighting reconstruction module. The system determines at least one of a three-dimensional (3D) position or a 3D orientation of a lighting unit based on a plurality of captured images of a mirror sphere. For each point light source in a plurality of point light sources included in the lighting unit, the system determines an intensity associated with the point light source. The system determines captures appearance data of the object, where the object is illuminated by the lighting unit. The system renders an image of the object based on the appearance data and the intensities associated with each point light source in the plurality of point light sources.

Abstract: Various embodiments include a system for rendering an object, such as human skin or a human head, from captured appearance data comprising a plurality of texels. The system includes a processor executing a texture space indirect illumination module. The system determines texture coordinates of a vector originating from a first texel where the vector intersects a second texel. The system renders the second texel from the viewpoint of the first texel based on appearance data at the second texel. Based on the rendering of the second texel, the system determines an indirect lighting intensity incident to the first texel from the second texel. The system updates appearance data at the first texel based on a direct lighting intensity and the indirect lighting intensity. The system renders the first texel based on the updated appearance data at the first texel.

Abstract: A technique for rendering an input geometry includes generating a first segmentation mask for a first input geometry and a first set of texture maps associated with one or more portions of the first input geometry. The technique also includes generating, via one or more neural networks, a first set of neural textures for the one or more portions of the first input geometry. The technique further includes rendering a first image corresponding to the first input geometry based on the first segmentation mask, the first set of texture maps, and the first set of neural textures.

Abstract: A technique for generating a sequence of geometries includes converting, via an encoder neural network, one or more input geometries corresponding to one or more frames within an animation into one or more latent vectors. The technique also includes generating the sequence of geometries corresponding to a sequence of frames within the animation based on the one or more latent vectors. The technique further includes causing output related to the animation to be generated based on the sequence of geometries.

Abstract: Techniques are disclosed for generating photorealistic images of objects, such as heads, from multiple viewpoints. In some embodiments, a morphable radiance field (MoRF) model that generates images of heads includes an identity model that maps an identifier (ID) code associated with a head into two codes: a deformation ID code encoding a geometric deformation from a canonical head geometry, and a canonical ID code encoding a canonical appearance within a shape-normalized space. The MoRF model also includes a deformation field model that maps a world space position to a shape-normalized space position based on the deformation ID code. Further, the MoRF model includes a canonical neural radiance field (NeRF) model that includes a density multi-layer perceptron (MLP) branch, a diffuse MLP branch, and a specular MLP branch that output densities, diffuse colors, and specular colors, respectively. The MoRF model can be used to render images of heads from various viewpoints.

Abstract: Techniques are disclosed for creating digital faces. In some examples, an anatomical face model is generated from a data set including captured facial geometries of different individuals and associated bone geometries. A model generator segments each of the captured facial geometries into patches, compresses the segmented geometry associated with each patch to determine local deformation subspaces of the anatomical face model, and determines corresponding compressed anatomical subspaces of the anatomical face model. A sculpting application determines, based on sculpting input from a user, constraints for an optimization to determine parameter values associated with the anatomical face model. The parameter values can be used, along with the anatomical face model, to generate facial geometry that reflects the sculpting input.

Abstract: One embodiment of the present invention sets forth a technique for performing appearance capture. The technique includes receiving a first sequence of images of an object, wherein the first sequence of images includes a first set of images interleaved with a second set of images, and wherein the first set of images is captured based on illumination of the object using a first lighting pattern and the second set of images is captured based on illumination of the object using one or more lighting patterns that are different from the first lighting pattern. The technique also includes generating a first set of appearance parameters associated with the object based on a first inverse rendering associated with the first sequence of images.

Abstract: A technique for synthesizing a shape includes generating a first plurality of offset tokens based on a first shape code and a first plurality of position tokens, wherein the first shape code represents a variation of a canonical shape, and wherein the first plurality of position tokens represent a first plurality of positions on the canonical shape. The technique also includes generating a first plurality of offsets associated with the first plurality of positions on the canonical shape based on the first plurality of offset tokens. The technique further includes generating the shape based on the first plurality of offsets and the first plurality of positions.