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公开(公告)号：US20240296645A1
公开(公告)日：2024-09-05
申请号：US18664596
申请日：2024-05-15
Applicant: Snap Inc.
Inventor： Vladislav Shakhrai , Sergey Demyanov , Mikhail Vasilkovskii , Aleksei Stoliar
CPC classification number: G06T19/20 , G06T7/40 , G06T11/001 , G06T17/20 , G06T2207/20081 , G06T2207/20084 , G06T2210/12 , G06T2210/22 , G06T2219/2016
Abstract: Methods and systems are disclosed for performing operations for generating a photorealistic rendering of an object. The operations include: accessing a set of albedo textures and a machine learning model associated with a real-world object, the set of albedo textures and a machine learning model having been trained based on a plurality of viewpoints of the real-world object; obtaining a three-dimensional (3D) mesh of the real-world object; receiving input that selects a new viewpoint that differs from the plurality of viewpoints of the real-world object; and generating a photorealistic rendering of the real-world object from the new viewpoint based on the 3D mesh of the real-world object, the set of albedo textures, and the machine learning model associated with the real-world object.
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公开(公告)号：US12020392B2
公开(公告)日：2024-06-25
申请号：US17855179
申请日：2022-06-30
Applicant: Snap Inc.
Inventor： Vladislav Shakhrai , Sergey Demyanov , Mikhail Vasilkovskii , Aleksei Stoliar
CPC classification number: G06T19/20 , G06T7/40 , G06T11/001 , G06T17/20 , G06T2207/20081 , G06T2207/20084 , G06T2210/12 , G06T2210/22 , G06T2219/2016
Abstract: Methods and systems are disclosed for performing operations for generating a photorealistic rendering of an object. The operations include: accessing a set of albedo textures and a machine learning model associated with a real-world object, the set of albedo textures and a machine learning model having been trained based on a plurality of viewpoints of the real-world object; obtaining a three-dimensional (3D) mesh of the real-world object; receiving input that selects a new viewpoint that differs from the plurality of viewpoints of the real-world object; and generating a photorealistic rendering of the real-world object from the new viewpoint based on the 3D mesh of the real-world object, the set of albedo textures, and the machine learning model associated with the real-world object.
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公开(公告)号：US20230410479A1
公开(公告)日：2023-12-21
申请号：US17841333
申请日：2022-06-15
Applicant: Snap Inc.
Inventor： Sergey Demyanov , Konstantin Gudkov , Fedor Zhdanov , Andrei Zharkov
CPC classification number: G06V10/774 , G06V10/82 , G06V10/74 , G06V40/16 , G06T3/0093 , G06T11/00 , G06T7/68 , G06T2207/20081 , G06T2207/20084 , G06T2207/30201 , G06T2207/20221
Abstract: An image manipulation system for generating modified images using a generative adversarial network (GAN) trains GANs using domain changes, aligns input images with generated images, classifies and associates target images based on a symmetry, and uses a modified discriminator structure. A method for domain changes includes generating, using a pre-trained GAN trained on a plurality of first target images, a plurality of images, and determining a feature for each of the plurality of images. The method further includes determining the feature for each of a plurality of second target images and matching, based on the feature, second target images of the plurality of second target images with the plurality of images. The method further includes training a discriminator of the pre-trained GAN with the second target images and the plurality of images.
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公开(公告)号：US20240246590A1
公开(公告)日：2024-07-25
申请号：US18625568
申请日：2024-04-03
Applicant: Snap Inc.
Inventor： Sergey Demyanov , Yunqing Hu , Istvan Marton , Daniil Ostashev , Aleksei Podkin
CPC classification number: B62B3/0618 , A47B9/20 , A47B31/00 , B62B5/0086 , B66F11/04 , B62B2202/30
Abstract: Systems and embodiments herein describe an augmented reality (AR) object rendering system. The AR object rendering system receives an image, generates a set of noise parameters and a set of blur parameters for the image using a neural network trained on a paired dataset of images, identifies an AR object associated with the image, modifies the AR object using the set of noise parameters and the set of blur parameters, displays the modified augmented reality object within the image.
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公开(公告)号：US11954810B2
公开(公告)日：2024-04-09
申请号：US17843573
申请日：2022-06-17
Applicant: Snap Inc.
Inventor： Sergey Demyanov , Yunqing Hu , Istvan Marton , Daniil Ostashev , Aleksei Podkin
CPC classification number: G06T19/006 , G06T5/002 , G06T5/20 , G06V10/774 , G06V10/82 , G06V20/20 , G06T2207/20081 , G06T2207/20084 , G06T2207/30201
Abstract: Systems and embodiments herein describe an augmented reality (AR) object rendering system. The AR object rendering system receives an image, generates a set of noise parameters and a set of blur parameters for the image using a neural network trained on a paired dataset of images, identifies an AR object associated with the image, modifies the AR object using the set of noise parameters and the set of blur parameters, displays the modified augmented reality object within the image.
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Patent Agency Ranking
公开(公告)号：US11900565B2
公开(公告)日：2024-02-13
申请号：US18116682
申请日：2023-03-02
Applicant: Snap Inc.
Inventor： Sergey Demyanov , Aleksei Podkin , Aleksei Stoliar , Vadim Velicodnii , Fedor Zhdanov
CPC classification number: G06T5/001 , G06T5/10 , G06T2200/16 , G06T2207/10004 , G06T2207/20048 , G06T2207/20081 , G06T2207/30196 , H04L51/10
Abstract: A data item is identified on a device. A neural network that includes an adversarial transformation subnetwork is applied to the data item to generate a modified data item. Output indicative of the modified data item is caused to be presented on the device. The neural network further comprises an encoder and a decoder. The neural network is trained in at least two stages. At least one of the encoder and the decoder is trained in a first stage and the adversarial transformation subnetwork is trained in a second stage.
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公开(公告)号：US20230419599A1
公开(公告)日：2023-12-28
申请号：US17846918
申请日：2022-06-22
Applicant: Snap Inc.
Inventor： Menglei Chai , Sergey Demyanov , Yunqing Hu , Istvan Marton , Daniil Ostashev , Aleksei Podkin
IPC: G06T15/50 , G06T15/80 , G06V10/82 , G06V10/774
CPC classification number: G06T15/506 , G06T15/80 , G06V10/82 , G06V10/774 , G06T2200/08 , G06T2200/04
Abstract: A method for applying lighting conditions to a virtual object in an augmented reality (AR) device is described. In one aspect, the method includes generating, using a camera of a mobile device, an image, accessing a virtual object corresponding to an object in the image, identifying lighting parameters of the virtual object based on a machine learning model that is pre-trained with a paired dataset, the paired dataset includes synthetic source data and synthetic target data, the synthetic source data includes environment maps and 3D scans of items depicted in the environment map, the synthetic target data includes a synthetic sphere image rendered in the same environment map, applying the lighting parameters to the virtual object, and displaying, in a display of the mobile device, the shaded virtual object as a layer to the image.
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公开(公告)号：US20230206398A1
公开(公告)日：2023-06-29
申请号：US18116682
申请日：2023-03-02
Applicant: Snap Inc.
Inventor： Sergey Demyanov , Aleksei Podkin , Aleksei Stoliar , Vadim Velicodnii , Fedor Zhdanov
CPC classification number: G06T5/001 , G06T5/10 , G06T2207/20081 , H04L51/10
Abstract: A data item is identified on a device. A neural network that includes an adversarial transformation subnetwork is applied to the data item to generate a modified data item. Output indicative of the modified data item is caused to be presented on the device. The neural network further comprises an encoder and a decoder. The neural network is trained in at least two stages. At least one of the encoder and the decoder is trained in a first stage and the adversarial transformation subnetwork is trained in a second stage.
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公开(公告)号：US20250037436A1
公开(公告)日：2025-01-30
申请号：US18911590
申请日：2024-10-10
Applicant: Snap Inc.
Inventor： Sergey Demyanov , Konstantin Gudkov , Fedor Zhdanov , Andrei Zharkov
Abstract: An image manipulation system for generating modified images using a generative adversarial network (GAN) trains GANs using domain changes, aligns input images with generated images, classifies and associates target images based on a symmetry, and uses a modified discriminator structure. A method for domain changes includes generating, using a pre-trained GAN trained on a plurality of first target images, a plurality of images, and determining a feature for each of the plurality of images. The method further includes determining the feature for each of a plurality of second target images and matching, based on the feature, second target images of the plurality of second target images with the plurality of images. The method further includes training a discriminator of the pre-trained GAN with the second target images and the plurality of images.
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公开(公告)号：US12125129B2
公开(公告)日：2024-10-22
申请号：US18136470
申请日：2023-04-19
Applicant: Snap Inc.
Inventor： Sergey Demyanov , Aleksei Podkin , Aliaksandr Siarohin , Aleksei Stoliar , Sergey Tulyakov
CPC classification number: G06T13/00 , G06N3/045 , G06N3/08 , G06V40/171 , G06V40/174
Abstract: Systems and methods are disclosed for generating, a source image sequence using an image sensor of the computing device, the source image sequence comprising a plurality of source images depicting a head and face, identifying driving image sequence data to modify face image feature data in the source image sequence, generating, using an image transformation neural network, a modified source image sequence comprising a plurality of modified source images depicting modified versions of the head and face, and storing the modified source image sequence on the computing device.
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