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公开(公告)号：US11682126B2
公开(公告)日：2023-06-20
申请号：US17080812
申请日：2020-10-26
Applicant: ADOBE INC.
Inventor： Kalyan Krishna Sunkavalli , Sunil Hadap , Joon-Young Lee , Zhuo Hui
CPC classification number: G06T7/49 , G01N21/55 , G06T3/0068 , G06T7/40 , G06T7/60 , G06T7/90 , G06T17/00 , G06T2200/08 , G06T2207/10016 , G06T2207/10152
Abstract: Methods and systems are provided for performing material capture to determine properties of an imaged surface. A plurality of images can be received depicting a material surface. The plurality of images can be calibrated to align corresponding pixels of the images and determine reflectance information for at least a portion of the aligned pixels. After calibration, a set of reference materials from a material library can be selected using the calibrated images. The set of reference materials can be used to determine a material model that accurately represents properties of the material surface.
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公开(公告)号：US11551388B2
公开(公告)日：2023-01-10
申请号：US16794908
申请日：2020-02-19
Applicant: Adobe Inc.
Inventor： Kalyan Krishna Sunkavalli , Nathan Aaron Carr , Michal Lukác , Elya Shechtman
Abstract: Image modification using detected symmetry is described. In example implementations, an image modification module detects multiple local symmetries in an original image by discovering repeated correspondences that are each related by a transformation. The transformation can include a translation, a rotation, a reflection, a scaling, or a combination thereof. Each repeated correspondence includes three patches that are similar to one another and are respectively defined by three pixels of the original image. The image modification module generates a global symmetry of the original image by analyzing an applicability to the multiple local symmetries of multiple candidate homographies contributed by the multiple local symmetries. The image modification module associates individual pixels of the original image with a global symmetry indicator to produce a global symmetry association map. The image modification module produces a manipulated image by manipulating the original image under global symmetry constraints imposed by the global symmetry association map.
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公开(公告)号：US10979640B2
公开(公告)日：2021-04-13
申请号：US16789195
申请日：2020-02-12
Applicant: Adobe Inc.
IPC: G06T5/00 , H04N5/232 , G06K9/46 , G06T15/50 , G06N3/08 , H04N5/235 , G06K9/00 , G06K9/62 , G06N3/04
Abstract: The present disclosure is directed toward systems and methods for predicting lighting conditions. In particular, the systems and methods described herein analyze a single low-dynamic range digital image to estimate a set of high-dynamic range lighting conditions associated with the single low-dynamic range lighting digital image. Additionally, the systems and methods described herein train a convolutional neural network to extrapolate lighting conditions from a digital image. The systems and methods also augment low-dynamic range information from the single low-dynamic range digital image by using a sky model algorithm to predict high-dynamic range lighting conditions.
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公开(公告)号：US20190311202A1
公开(公告)日：2019-10-10
申请号：US15949935
申请日：2018-04-10
Applicant: Adobe Inc.
Inventor： Joon-Young Lee , Seoungwug Oh , Kalyan Krishna Sunkavalli
Abstract: Various embodiments describe video object segmentation using a neural network and the training of the neural network. The neural network both detects a target object in the current frame based on a reference frame and a reference mask that define the target object and propagates the segmentation mask of the target object for a previous frame to the current frame to generate a segmentation mask for the current frame. In some embodiments, the neural network is pre-trained using synthetically generated static training images and is then fine-tuned using training videos.
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公开(公告)号：US20190228567A1
公开(公告)日：2019-07-25
申请号：US15877142
申请日：2018-01-22
Applicant: ADOBE INC.
Inventor： Jeong Joon Park , Zhili Chen , Xin Sun , Vladimir Kim , Kalyan Krishna Sunkavalli , Duygu Ceylan Aksit
Abstract: Matching an illumination of an embedded virtual object (VO) with current environment illumination conditions provides an enhanced immersive experience to a user. To match the VO and environment illuminations, illumination basis functions are determined based on preprocessing image data, captured as a first combination of intensities of direct illumination sources illuminates the environment. Each basis function corresponds to one of the direct illumination sources. During the capture of runtime image data, a second combination of intensities illuminates the environment. An illumination-weighting vector is determined based on the runtime image data. The determination of the weighting vector accounts for indirect illumination sources, such as surface reflections. The weighting vector encodes a superposition of the basis functions that corresponds to the second combination of intensities. The method illuminates the VO based on the weighting vector. The resulting illumination of the VO matches the second combination of the intensities and surface reflections.
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Patent Agency Ranking
公开(公告)号：US11488342B1
公开(公告)日：2022-11-01
申请号：US17332708
申请日：2021-05-27
Applicant: ADOBE INC.
Inventor： Kalyan Krishna Sunkavalli , Yannick Hold-Geoffroy , Milos Hasan , Zexiang Xu , Yu-Ying Yeh , Stefano Corazza
Abstract: 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).
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7.发明申请公开(公告)号：US20220343522A1
公开(公告)日：2022-10-27
申请号：US17233122
申请日：2021-04-16
Applicant: ADOBE INC.
Inventor： Sai Bi , Zexiang Xu , Kalyan Krishna Sunkavalli , David Jay Kriegman , Ravi Ramamoorthi
IPC: G06T7/514 , G06T17/20 , H04N13/111 , H04N13/128 , H04N13/282
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.
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公开(公告)号：US20220335636A1
公开(公告)日：2022-10-20
申请号：US17231833
申请日：2021-04-15
Applicant: ADOBE INC.
Inventor： Sai Bi , Zexiang Xu , Kalyan Krishna Sunkavalli , Milos Hasan , Yannick Hold-Geoffroy , David Jay Kriegman , Ravi Ramamoorthi
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).
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公开(公告)号：US11176381B2
公开(公告)日：2021-11-16
申请号：US16856292
申请日：2020-04-23
Applicant: Adobe Inc.
Inventor： Joon-Young Lee , Seoungwug Oh , Kalyan Krishna Sunkavalli
Abstract: Various embodiments describe video object segmentation using a neural network and the training of the neural network. The neural network both detects a target object in the current frame based on a reference frame and a reference mask that define the target object and propagates the segmentation mask of the target object for a previous frame to the current frame to generate a segmentation mask for the current frame. In some embodiments, the neural network is pre-trained using synthetically generated static training images and is then fine-tuned using training videos.
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公开(公告)号：US20200184697A1
公开(公告)日：2020-06-11
申请号：US16794908
申请日：2020-02-19
Applicant: Adobe Inc.
Inventor： Kalyan Krishna Sunkavalli , Nathan Aaron Carr , Michal Lukác , Elya Shechtman
Abstract: Image modification using detected symmetry is described. In example implementations, an image modification module detects multiple local symmetries in an original image by discovering repeated correspondences that are each related by a transformation. The transformation can include a translation, a rotation, a reflection, a scaling, or a combination thereof. Each repeated correspondence includes three patches that are similar to one another and are respectively defined by three pixels of the original image. The image modification module generates a global symmetry of the original image by analyzing an applicability to the multiple local symmetries of multiple candidate homographies contributed by the multiple local symmetries. The image modification module associates individual pixels of the original image with a global symmetry indicator to produce a global symmetry association map. The image modification module produces a manipulated image by manipulating the original image under global symmetry constraints imposed by the global symmetry association map.
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