Patents by Inventor Milos Hasan
Milos Hasan has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
-
Publication number: 20240062455Abstract: Embodiments are disclosed for performing 3-D vectorization. The method includes obtaining a three-dimensional rendered image and a camera position. The method further includes obtaining a triangle mesh representing the three-dimensional rendered image. The method further involves creating a reduced triangle mesh by removing one or more triangles from the triangle mesh. The method further involves subdividing each triangle of the reduced triangle mesh into one or more subdivided triangles. The method further involves performing a mapping of each pixel of the three-dimensional rendered image to the reduced triangle mesh. The method further involves assigning a color value to each vertex of the reduced triangle mesh. The method further involves sorting each triangle of the reduced triangle mesh using a depth value of each triangle. The method further involves generating a two-dimensional triangle mesh using the sorted triangles of the reduced triangle mesh.Type: ApplicationFiled: August 16, 2022Publication date: February 22, 2024Applicant: Adobe Inc.Inventors: Ankit PHOGAT, Xin SUN, Vineet BATRA, Sumit DHINGRA, Nathan A. CARR, Milos HASAN
-
Patent number: 11887241Abstract: Embodiments are disclosed for neural texture mapping. In some embodiments, a method of neural texture mapping includes obtaining a plurality of images of an object, determining volumetric representation of a scene of the object using a first neural network, mapping 3D points of the scene to a 2D texture space using a second neural network, and determining radiance values for each 2D point in the 2D texture space from a plurality of viewpoints using a second neural network to generate a 3D appearance representation of the object.Type: GrantFiled: December 22, 2021Date of Patent: January 30, 2024Assignee: Adobe Inc.Inventors: Zexiang Xu, Yannick Hold-Geoffroy, Milos Hasan, Kalyan Sunkavalli, Fanbo Xiang
-
Publication number: 20240020916Abstract: Embodiments are disclosed for optimizing a material graph for replicating a material of the target image. Embodiments include receiving a target image and a material graph to be optimized for replicating a material of the target image. Embodiments include identifying a non-differentiable node of the material graph, the non-differentiable node including a set of input parameters. Embodiments include selecting a differentiable proxy from a library of the selected differentiable proxy is trained to replicate an output of the identified non-differentiable node. Embodiments include generating an optimized input parameters for the identified non-differentiable node using the corresponding trained neural network and the target image. Embodiments include replacing the set of input parameters of the non-differentiable node of the material graph with the optimized input parameters.Type: ApplicationFiled: July 14, 2022Publication date: January 18, 2024Applicant: Adobe Inc.Inventors: Valentin DESCHAINTRE, Yiwei HU, Paul GUERRERO, Milos HASAN
-
Patent number: 11875446Abstract: Aspects of a system and method for procedural media generation include generating a sequence of operator types using a node generation network; generating a sequence of operator parameters for each operator type of the sequence of operator types using a parameter generation network; generating a sequence of directed edges based on the sequence of operator types using an edge generation network; combining the sequence of operator types, the sequence of operator parameters, and the sequence of directed edges to obtain a procedural media generator, wherein each node of the procedural media generator comprises an operator that includes an operator type from the sequence of operator types, a corresponding sequence of operator parameters, and an input connection or an output connection from the sequence of directed edges that connects the node to another node of the procedural media generator; and generating a media asset using the procedural media generator.Type: GrantFiled: May 6, 2022Date of Patent: January 16, 2024Assignee: ADOBE, INC.Inventors: Paul Augusto Guerrero, Milos Hasan, Kalyan K. Sunkavalli, Radomir Mech, Tamy Boubekeur, Niloy Jyoti Mitra
-
Patent number: 11816779Abstract: Methods and systems disclosed herein relate generally to surface-rendering neural networks to represent and render a variety of material appearances (e.g., textured surfaces) at different scales. The system includes receiving image metadata for a texel that includes position, incoming and outgoing radiance direction, and a kernel size. The system applies a offset-prediction neural network to the query to identify an offset coordinate for the texel. The system inputs the offset coordinate to a data structure to determine a feature vector for the texel of the textured surface. The reflectance feature vector is then processed using a decoder neural network to estimate a light-reflectance value of the texel, at which the light-reflectance value is used to render the texel of the textured surface.Type: GrantFiled: November 30, 2021Date of Patent: November 14, 2023Assignees: Adobe Inc., The Regents of the University of CaliforniaInventors: Krishna Bhargava Mullia Lakshminarayana, Zexiang Xu, Milos Hasan, Ravi Ramamoorthi, Alexandr Kuznetsov
-
Publication number: 20230360310Abstract: Aspects of a system and method for procedural media generation include generating a sequence of operator types using a node generation network; generating a sequence of operator parameters for each operator type of the sequence of operator types using a parameter generation network; generating a sequence of directed edges based on the sequence of operator types using an edge generation network; combining the sequence of operator types, the sequence of operator parameters, and the sequence of directed edges to obtain a procedural media generator, wherein each node of the procedural media generator comprises an operator that includes an operator type from the sequence of operator types, a corresponding sequence of operator parameters, and an input connection or an output connection from the sequence of directed edges that connects the node to another node of the procedural media generator; and generating a media asset using the procedural media generator.Type: ApplicationFiled: May 6, 2022Publication date: November 9, 2023Inventors: Paul Augusto Guerrero, Milos Hasan, Kalyan K. Sunkavalli, Radomir Mech, Tamy Boubekeur, Niloy Jyoti Mitra
-
Publication number: 20230360285Abstract: The present disclosure relates to using end-to-end differentiable pipeline for optimizing parameters of a base procedural material to generate a procedural material corresponding to a target physical material. For example, the disclosed systems can receive a digital image of a target physical material. In response, the disclosed systems can retrieve a differentiable procedural material for use as a base procedural material in response. The disclosed systems can compare a digital image of the base procedural material with the digital image of the target physical material using a loss function, such as a style loss function that compares visual appearance. Based on the determined loss, the disclosed systems can modify the parameters of the base procedural material to determine procedural material parameters for the target physical material. The disclosed systems can generate a procedural material corresponding to the base procedural material using the determined procedural material parameters.Type: ApplicationFiled: June 26, 2023Publication date: November 9, 2023Inventors: Milos Hasan, Liang Shi, Tamy Boubekeur, Kalyan Sunkavalli, Radomir Mech
-
Patent number: 11688109Abstract: The present disclosure relates to using end-to-end differentiable pipeline for optimizing parameters of a base procedural material to generate a procedural material corresponding to a target physical material. For example, the disclosed systems can receive a digital image of a target physical material. In response, the disclosed systems can retrieve a differentiable procedural material for use as a base procedural material in response. The disclosed systems can compare a digital image of the base procedural material with the digital image of the target physical material using a loss function, such as a style loss function that compares visual appearance. Based on the determined loss, the disclosed systems can modify the parameters of the base procedural material to determine procedural material parameters for the target physical material. The disclosed systems can generate a procedural material corresponding to the base procedural material using the determined procedural material parameters.Type: GrantFiled: October 28, 2021Date of Patent: June 27, 2023Assignee: Adobe Inc.Inventors: Milos Hasan, Liang Shi, Tamy Boubekeur, Kalyan Sunkavalli, Radomir Mech
-
Publication number: 20230169715Abstract: Methods and systems disclosed herein relate generally to surface-rendering neural networks to represent and render a variety of material appearances (e.g., textured surfaces) at different scales. The system includes receiving image metadata for a texel that includes position, incoming and outgoing radiance direction, and a kernel size. The system applies a offset-prediction neural network to the query to identify an offset coordinate for the texel. The system inputs the offset coordinate to a data structure to determine a feature vector for the texel of the textured surface. The reflectance feature vector is then processed using a decoder neural network to estimate a light-reflectance value of the texel, at which the light-reflectance value is used to render the texel of the textured surface.Type: ApplicationFiled: November 30, 2021Publication date: June 1, 2023Inventors: Krishna Bhargava Mullia Lakshminarayana, Zexiang Xu, Milos Hasan, Ravi Ramamoorthi, Alexandr Kuznetsov
-
Patent number: 11663775Abstract: Methods, system, and computer storage media are provided for generating physical-based materials for rendering digital objects with an appearance of a real-world material. Images depicted the real-world material, including diffuse component images and specular component images, are captured using different lighting patterns, which may include area lights. From the captured images, approximations of one or more material maps are determined using a photometric stereo technique. Based on the approximations and the captured images, a neural network system generates a set of material maps, such as a diffuse albedo material map, a normal material map, a specular albedo material map, and a roughness material map. The material maps from the neural network may be optimized based on a comparison of the input images of the real-world material and images rendered from the material maps.Type: GrantFiled: April 19, 2021Date of Patent: May 30, 2023Assignee: Adobe, Inc.Inventors: Akshat Dave, Kalyan Krishna Sunkavalli, Yannick Hold-Geoffroy, Milos Hasan
-
Patent number: 11657562Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods that utilize hemispherical clamping for importance sampling of an image-based light (IBL) to generate a digital image of a virtual environment. For example, the disclosed systems identify a hemispherical portion of an IBL image that corresponds to a reflective surface location on a virtual object. The disclosed systems can then clamp the IBL image using one or more importance sampling algorithms to exclude portions of the IBL image outside of the hemispherical portion that do not contribute direct lighting onto the reflective surface location. The disclosed systems can further utilize the one or more importance sampling algorithms to efficiently sample a ray direction between the reflective surface location and the hemispherical portion of the IBL image. In certain embodiments, the disclosed systems use the sampled ray direction to generate a digital image rendering portraying the virtual object.Type: GrantFiled: April 19, 2021Date of Patent: May 23, 2023Assignee: Adobe Inc.Inventors: Xin Sun, Milos Hasan, Nathan Carr
-
Patent number: 11488342Abstract: Embodiments of the technology described herein, make unknown material-maps in a Physically Based Rendering (PBR) asset usable through an identification process that relies, at least in part, on image analysis. In addition, when a desired material-map type is completely missing from a PBR asset the technology described herein may generate a suitable synthetic material map for use in rendering. In one aspect, the correct map type is assigned using a machine classifier, such as a convolutional neural network, which analyzes image content of the unknown material map and produce a classification. The technology described herein also correlates material maps into material definitions using a combination of the material-map type and similarity analysis. The technology described herein may generate synthetic maps to be used in place of the missing material maps. The synthetic maps may be generated using a Generative Adversarial Network (GAN).Type: GrantFiled: May 27, 2021Date of Patent: November 1, 2022Assignee: ADOBE INC.Inventors: Kalyan Krishna Sunkavalli, Yannick Hold-Geoffroy, Milos Hasan, Zexiang Xu, Yu-Ying Yeh, Stefano Corazza
-
Publication number: 20220335682Abstract: Methods, system, and computer storage media are provided for generating physical-based materials for rendering digital objects with an appearance of a real-world material. Images depicted the real-world material, including diffuse component images and specular component images, are captured using different lighting patterns, which may include area lights. From the captured images, approximations of one or more material maps are determined using a photometric stereo technique. Based on the approximations and the captured images, a neural network system generates a set of material maps, such as a diffuse albedo material map, a normal material map, a specular albedo material map, and a roughness material map. The material maps from the neural network may be optimized based on a comparison of the input images of the real-world material and images rendered from the material maps.Type: ApplicationFiled: April 19, 2021Publication date: October 20, 2022Inventors: Akshat Dave, Kalyan Krishna Sunkavalli, Yannick Hold-Geoffroy, Milos Hasan
-
Publication number: 20220335636Abstract: 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).Type: ApplicationFiled: April 15, 2021Publication date: October 20, 2022Inventors: Sai Bi, Zexiang Xu, Kalyan Krishna Sunkavalli, Milos Hasan, Yannick Hold-Geoffroy, David Jay Kriegman, Ravi Ramamoorthi
-
Publication number: 20220335677Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods that utilize hemispherical clamping for importance sampling of an image-based light (IBL) to generate a digital image of a virtual environment. For example, the disclosed systems identify a hemispherical portion of an IBL image that corresponds to a reflective surface location on a virtual object. The disclosed systems can then clamp the IBL image using one or more importance sampling algorithms to exclude portions of the IBL image outside of the hemispherical portion that do not contribute direct lighting onto the reflective surface location. The disclosed systems can further utilize the one or more importance sampling algorithms to efficiently sample a ray direction between the reflective surface location and the hemispherical portion of the IBL image. In certain embodiments, the disclosed systems use the sampled ray direction to generate a digital image rendering portraying the virtual object.Type: ApplicationFiled: April 19, 2021Publication date: October 20, 2022Inventors: Xin Sun, Milos Hasan, Nathan Carr
-
Publication number: 20220198738Abstract: Embodiments are disclosed for neural texture mapping. In some embodiments, a method of neural texture mapping includes obtaining a plurality of images of an object, determining volumetric representation of a scene of the object using a first neural network, mapping 3D points of the scene to a 2D texture space using a second neural network, and determining radiance values for each 2D point in the 2D texture space from a plurality of viewpoints using a second neural network to generate a 3D appearance representation of the object.Type: ApplicationFiled: December 22, 2021Publication date: June 23, 2022Applicant: Adobe Inc.Inventors: Zexiang XU, Yannick HOLD-GEOFFROY, Milos HASAN, Kalyan SUNKAVALLI, Fanbo XIANG
-
Publication number: 20220051453Abstract: The present disclosure relates to using end-to-end differentiable pipeline for optimizing parameters of a base procedural material to generate a procedural material corresponding to a target physical material. For example, the disclosed systems can receive a digital image of a target physical material. In response, the disclosed systems can retrieve a differentiable procedural material for use as a base procedural material in response. The disclosed systems can compare a digital image of the base procedural material with the digital image of the target physical material using a loss function, such as a style loss function that compares visual appearance. Based on the determined loss, the disclosed systems can modify the parameters of the base procedural material to determine procedural material parameters for the target physical material. The disclosed systems can generate a procedural material corresponding to the base procedural material using the determined procedural material parameters.Type: ApplicationFiled: October 28, 2021Publication date: February 17, 2022Inventors: Milos Hasan, Liang Shi, Tamy Boubekeur, Kalyan Sunkavalli, Radomir Mech
-
Patent number: 11189060Abstract: The present disclosure relates to using end-to-end differentiable pipeline for optimizing parameters of a base procedural material to generate a procedural material corresponding to a target physical material. For example, the disclosed systems can receive a digital image of a target physical material. In response, the disclosed systems can retrieve a differentiable procedural material for use as a base procedural material in response. The disclosed systems can compare a digital image of the base procedural material with the digital image of the target physical material using a loss function, such as a style loss function that compares visual appearance. Based on the determined loss, the disclosed systems can modify the parameters of the base procedural material to determine procedural material parameters for the target physical material. The disclosed systems can generate a procedural material corresponding to the base procedural material using the determined procedural material parameters.Type: GrantFiled: April 30, 2020Date of Patent: November 30, 2021Assignee: ADOBE INC.Inventors: Milos Hasan, Liang Shi, Tamy Boubekeur, Kalyan Sunkavalli, Radomir Mech
-
Publication number: 20210343051Abstract: The present disclosure relates to using end-to-end differentiable pipeline for optimizing parameters of a base procedural material to generate a procedural material corresponding to a target physical material. For example, the disclosed systems can receive a digital image of a target physical material. In response, the disclosed systems can retrieve a differentiable procedural material for use as a base procedural material in response. The disclosed systems can compare a digital image of the base procedural material with the digital image of the target physical material using a loss function, such as a style loss function that compares visual appearance. Based on the determined loss, the disclosed systems can modify the parameters of the base procedural material to determine procedural material parameters for the target physical material. The disclosed systems can generate a procedural material corresponding to the base procedural material using the determined procedural material parameters.Type: ApplicationFiled: April 30, 2020Publication date: November 4, 2021Inventors: Milos Hasan, Liang Shi, Tamy Boubekeur, Kalyan Sunkavalli, Radomir Mech