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公开(公告)号:US20240312118A1
公开(公告)日:2024-09-19
申请号:US18185230
申请日:2023-03-16
Applicant: Adobe Inc. , The Regents of the University of California
Inventor: Zexiang XU , Xiaoshuai ZHANG , Sai BI , Kalyan SUNKAVALLI , Hao SU
CPC classification number: G06T15/08 , G06T15/06 , G06T15/205
Abstract: Embodiments are disclosed for fast large-scale radiance field reconstruction. A method of fast large-scale radiance field reconstruction may include receiving a sequence of input images that depict views of a scene and extracting, using an image encoder, image features from the sequence of input images. A first one or more machine learning models may generate a local volume based on the image features corresponding to one or more images from the sequence of input images. A second one or more machine learning models may generate a global volume based on the local volume. A novel view of the scene is synthesized based on the global volume.
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公开(公告)号:US20240177399A1
公开(公告)日:2024-05-30
申请号:US18426084
申请日:2024-01-29
Applicant: Adobe Inc.
Inventor: Zexiang XU , Yannick HOLD-GEOFFROY , Milos HASAN , Kalyan SUNKAVALLI , Fanbo XIANG
Abstract: 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.
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公开(公告)号:US20220198738A1
公开(公告)日:2022-06-23
申请号:US17559867
申请日:2021-12-22
Applicant: Adobe Inc.
Inventor: Zexiang XU , Yannick HOLD-GEOFFROY , Milos HASAN , Kalyan SUNKAVALLI , Fanbo XIANG
Abstract: 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.
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