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公开(公告)号：US11657562B2
公开(公告)日：2023-05-23
申请号：US17233910
申请日：2021-04-19
Applicant: Adobe Inc.
Inventor： Xin Sun , Milos Hasan , Nathan Carr
CPC classification number: G06T15/06 , G06T1/20 , G06T7/507 , G06T7/536 , G06T15/005
Abstract: 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.
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公开(公告)号：US20220122221A1
公开(公告)日：2022-04-21
申请号：US17384357
申请日：2021-07-23
Applicant: Adobe Inc.
Inventor： Cameron Smith , Ratheesh Kalarot , Wei-An Lin , Richard Zhang , Niloy Mitra , Elya Shechtman , Shabnam Ghadar , Zhixin Shu , Yannick Hold-Geoffrey , Nathan Carr , Jingwan Lu , Oliver Wang , Jun-Yan Zhu
IPC: G06T3/40 , G06F3/0484 , G06N3/08 , G06N3/04
Abstract: An improved system architecture uses a pipeline including a Generative Adversarial Network (GAN) including a generator neural network and a discriminator neural network to generate an image. An input image in a first domain and information about a target domain are obtained. The domains correspond to image styles. An initial latent space representation of the input image is produced by encoding the input image. An initial output image is generated by processing the initial latent space representation with the generator neural network. Using the discriminator neural network, a score is computed indicating whether the initial output image is in the target domain. A loss is computed based on the computed score. The loss is minimized to compute an updated latent space representation. The updated latent space representation is processed with the generator neural network to generate an output image in the target domain.
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公开(公告)号：US11158117B2
公开(公告)日：2021-10-26
申请号：US16877227
申请日：2020-05-18
Applicant: ADOBE INC.
Inventor： Kalyan Sunkavalli , Sunil Hadap , Nathan Carr , Mathieu Garon
Abstract: This disclosure relates to methods, non-transitory computer readable media, and systems that use a local-lighting-estimation-neural network to estimate lighting parameters for specific positions within a digital scene for augmented reality. For example, based on a request to render a virtual object in a digital scene, a system uses a local-lighting-estimation-neural network to generate location-specific-lighting parameters for a designated position within the digital scene. In certain implementations, the system also renders a modified digital scene comprising the virtual object at the designated position according to the parameters. In some embodiments, the system generates such location-specific-lighting parameters to spatially vary and adapt lighting conditions for different positions within a digital scene. As requests to render a virtual object come in real (or near real) time, the system can quickly generate different location-specific-lighting parameters that accurately reflect lighting conditions at different positions within a digital scene in response to render requests.
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公开(公告)号：US10692277B1
公开(公告)日：2020-06-23
申请号：US16360901
申请日：2019-03-21
Applicant: Adobe Inc.
Inventor： Kalyan Sunkavalli , Sunil Hadap , Nathan Carr , Mathieu Garon
Abstract: This disclosure relates to methods, non-transitory computer readable media, and systems that use a local-lighting-estimation-neural network to estimate lighting parameters for specific positions within a digital scene for augmented reality. For example, based on a request to render a virtual object in a digital scene, a system uses a local-lighting-estimation-neural network to generate location-specific-lighting parameters for a designated position within the digital scene. In certain implementations, the system also renders a modified digital scene comprising the virtual object at the designated position according to the parameters. In some embodiments, the system generates such location-specific-lighting parameters to spatially vary and adapt lighting conditions for different positions within a digital scene. As requests to render a virtual object come in real (or near real) time, the system can quickly generate different location-specific-lighting parameters that accurately reflect lighting conditions at different positions within a digital scene in response to render requests.
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公开(公告)号：US10650599B2
公开(公告)日：2020-05-12
申请号：US16029205
申请日：2018-07-06
Applicant: Adobe Inc.
Inventor： Xin Sun , Nathan Carr , Hao Qin
Abstract: The present disclosure includes methods and systems for rendering digital images of a virtual environment utilizing full path space learning. In particular, one or more embodiments of the disclosed systems and methods estimate a global light transport function based on sampled paths within a virtual environment. Moreover, in one or more embodiments, the disclosed systems and methods utilize the global light transport function to sample additional paths. Accordingly, the disclosed systems and methods can iteratively update an estimated global light transport function and utilize the estimated global light transport function to focus path sampling on regions of a virtual environment most likely to impact rendering a digital image of the virtual environment from a particular camera perspective.
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Patent Agency Ranking
公开(公告)号：US10290146B2
公开(公告)日：2019-05-14
申请号：US15335069
申请日：2016-10-26
Applicant: ADOBE INC.
Inventor： Zhili Chen , Xin Sun , Nathan Carr
Abstract: Techniques disclosed herein display depth effects in digital artwork based on movement of a display. In one technique, a first rendering of the digital artwork is displayed on the display. While the first rendering is displayed, a movement of the display is determined based on motion information from a motion sensor associated with the display. Based on the movement of the display, a position of the digital artwork is determined relative to a fixed gaze direction and a fixed light direction in a 3 dimensional (3D) model. A second rendering of the digital artwork is displayed on the display on the artwork. Displaying the second rendering involves displaying a depth effect based on variable depth of the digital artwork and the position of the digital artwork relative to the fixed gaze direction and the fixed light direction in the 3D model.
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公开(公告)号：US20220335677A1
公开(公告)日：2022-10-20
申请号：US17233910
申请日：2021-04-19
Applicant: Adobe Inc.
Inventor： Xin Sun , Milos Hasan , Nathan Carr
Abstract: 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.
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公开(公告)号：US11037019B2
公开(公告)日：2021-06-15
申请号：US15906783
申请日：2018-02-27
Applicant: Adobe Inc.
Inventor： Xin Sun , Sohrab Amirghodsi , Nathan Carr , Michal Lukac
Abstract: The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating a modified digital image by identifying patch matches within a digital image utilizing a Gaussian mixture model. For example, the systems described herein can identify sample patches and corresponding matching portions within a digital image. The systems can also identify transformations between the sample patches and the corresponding matching portions. Based on the transformations, the systems can generate a Gaussian mixture model, and the systems can modify a digital image by replacing a target region with target matching portions identified in accordance with the Gaussian mixture model.
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公开(公告)号：US10964100B2
公开(公告)日：2021-03-30
申请号：US16126552
申请日：2018-09-10
Applicant: Adobe Inc.
Inventor： Xin Sun , Zhili Chen , Nathan Carr , Julio Marco Murria , Jimei Yang
Abstract: According to one general aspect, systems and techniques for rendering a painting stroke of a three-dimensional digital painting include receiving a painting stroke input on a canvas, where the painting stroke includes a plurality of pixels. For each of the pixels in the plurality of pixels, a neighborhood patch of pixels is selected and input into a neural network and a shading function is output from the neural network. The painting stroke is rendered on the canvas using the shading function.
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公开(公告)号：US20200302684A1
公开(公告)日：2020-09-24
申请号：US16877227
申请日：2020-05-18
Applicant: ADOBE INC.
Inventor： Kalyan Sunkavalli , Sunil Hadap , Nathan Carr , Mathieu Garon
Abstract: This disclosure relates to methods, non-transitory computer readable media, and systems that use a local-lighting-estimation-neural network to estimate lighting parameters for specific positions within a digital scene for augmented reality. For example, based on a request to render a virtual object in a digital scene, a system uses a local-lighting-estimation-neural network to generate location-specific-lighting parameters for a designated position within the digital scene. In certain implementations, the system also renders a modified digital scene comprising the virtual object at the designated position according to the parameters. In some embodiments, the system generates such location-specific-lighting parameters to spatially vary and adapt lighting conditions for different positions within a digital scene. As requests to render a virtual object come in real (or near real) time, the system can quickly generate different location-specific-lighting parameters that accurately reflect lighting conditions at different positions within a digital scene in response to render requests.
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