-
公开(公告)号：US12182940B2
公开(公告)日：2024-12-31
申请号：US17578051
申请日：2022-01-18
Applicant: NVIDIA Corporation
Inventor： Xueting Li , Sifei Liu , Kihwan Kim , Shalini De Mello , Varun Jampani , Jan Kautz
IPC: G06T15/00 , G06F18/21 , G06T7/40 , G06T7/73 , G06T17/20 , G06V10/26 , G06V10/776 , G06V10/82 , G06V20/64
Abstract: Apparatuses, systems, and techniques to identify a shape or camera pose of a three-dimensional object from a two-dimensional image of the object. In at least one embodiment, objects are identified in an image using one or more neural networks that have been trained on objects of a similar category and a three-dimensional mesh template.
-
公开(公告)号：US11704857B2
公开(公告)日：2023-07-18
申请号：US17734244
申请日：2022-05-02
Applicant: NVIDIA Corporation
Inventor： Xueting Li , Sifei Liu , Kihwan Kim , Shalini De Mello , Jan Kautz
CPC classification number: G06T15/04 , G06T7/579 , G06T7/70 , G06T15/20 , G06T17/20 , G06T2207/10016 , G06T2207/20084 , G06T2207/30244
Abstract: A three-dimensional (3D) object reconstruction neural network system learns to predict a 3D shape representation of an object from a video that includes the object. The 3D reconstruction technique may be used for content creation, such as generation of 3D characters for games, movies, and 3D printing. When 3D characters are generated from video, the content may also include motion of the character, as predicted based on the video. The 3D object construction technique exploits temporal consistency to reconstruct a dynamic 3D representation of the object from an unlabeled video. Specifically, an object in a video has a consistent shape and consistent texture across multiple frames. Texture, base shape, and part correspondence invariance constraints may be applied to fine-tune the neural network system. The reconstruction technique generalizes well—particularly for non-rigid objects.
-
公开(公告)号：US20240404174A1
公开(公告)日：2024-12-05
申请号：US18653723
申请日：2024-05-02
Applicant: NVIDIA Corporation
Inventor： Xueting Li , Shalini De Mello , Sifei Liu , Koki Nagano , Umar Iqbal , Jan Kautz
Abstract: Systems and methods are disclosed that animate a source portrait image with motion (i.e., pose and expression) from a target image. In contrast to conventional systems, given an unseen single-view portrait image, an implicit three-dimensional (3D) head avatar is constructed that not only captures photo-realistic details within and beyond the face region, but also is readily available for animation without requiring further optimization during inference. In an embodiment, three processing branches of a system produce three tri-planes representing coarse 3D geometry for the head avatar, detailed appearance of a source image, as well as the expression of a target image. By applying volumetric rendering to a combination of the three tri-planes, an image of the desired identity, expression and pose is generated.
-
公开(公告)号：US20220036635A1
公开(公告)日：2022-02-03
申请号：US16945455
申请日：2020-07-31
Applicant: NVIDIA Corporation
Inventor： Xueting Li , Sifei Liu , Kihwan Kim , Shalini De Mello , Jan Kautz
Abstract: A three-dimensional (3D) object reconstruction neural network system learns to predict a 3D shape representation of an object from a video that includes the object. The 3D reconstruction technique may be used for content creation, such as generation of 3D characters for games, movies, and 3D printing. When 3D characters are generated from video, the content may also include motion of the character, as predicted based on the video. The 3D object construction technique exploits temporal consistency to reconstruct a dynamic 3D representation of the object from an unlabeled video. Specifically, an object in a video has a consistent shape and consistent texture across multiple frames. Texture, base shape, and part correspondence invariance constraints may be applied to fine-tune the neural network system. The reconstruction technique generalizes well—particularly for non-rigid objects.
-
公开(公告)号：US20230290038A1
公开(公告)日：2023-09-14
申请号：US18320446
申请日：2023-05-19
Applicant: NVIDIA Corporation
Inventor： Xueting Li , Sifei Liu , Kihwan Kim , Shalini De Mello , Jan Kautz
CPC classification number: G06T15/04 , G06T7/579 , G06T7/70 , G06T17/20 , G06T15/20 , G06T2207/30244 , G06T2207/20084 , G06T2207/10016
Abstract: A three-dimensional (3D) object reconstruction neural network system learns to predict a 3D shape representation of an object from a video that includes the object. The 3D reconstruction technique may be used for content creation, such as generation of 3D characters for games, movies, and 3D printing. When 3D characters are generated from video, the content may also include motion of the character, as predicted based on the video. The 3D object construction technique exploits temporal consistency to reconstruct a dynamic 3D representation of the object from an unlabeled video. Specifically, an object in a video has a consistent shape and consistent texture across multiple frames. Texture, base shape, and part correspondence invariance constraints may be applied to fine-tune the neural network system. The reconstruction technique generalizes well—particularly for non-rigid objects.
-
Patent Agency Ranking
公开(公告)号：US20220396289A1
公开(公告)日：2022-12-15
申请号：US17348604
申请日：2021-06-15
Applicant: NVIDIA Corporation
Inventor： Xueting Li , Sifei Liu , Shalini De Mello , Jan Kautz
Abstract: Apparatuses, systems, and techniques to calculate a plurality of paths, through which an autonomous device is to traverse. In at least one embodiment, a plurality of paths are calculated using one or more neural networks based, at least in part, on one or more distance values output by the one or more neural networks.
-
公开(公告)号：US11354847B2
公开(公告)日：2022-06-07
申请号：US16945455
申请日：2020-07-31
Applicant: NVIDIA Corporation
Inventor： Xueting Li , Sifei Liu , Kihwan Kim , Shalini De Mello , Jan Kautz
Abstract: A three-dimensional (3D) object reconstruction neural network system learns to predict a 3D shape representation of an object from a video that includes the object. The 3D reconstruction technique may be used for content creation, such as generation of 3D characters for games, movies, and 3D printing. When 3D characters are generated from video, the content may also include motion of the character, as predicted based on the video. The 3D object construction technique exploits temporal consistency to reconstruct a dynamic 3D representation of the object from an unlabeled video. Specifically, an object in a video has a consistent shape and consistent texture across multiple frames. Texture, base shape, and part correspondence invariance constraints may be applied to fine-tune the neural network system. The reconstruction technique generalizes well—particularly for non-rigid objects.
-
公开(公告)号：US20240070987A1
公开(公告)日：2024-02-29
申请号：US18110287
申请日：2023-02-15
Applicant: NVIDIA Corporation
Inventor： Xueting Li , Sifei Liu , Shalini De Mello , Orazio Gallo , Jiashun Wang , Jan Kautz
Abstract: Transferring pose to three-dimensional characters is a common computer graphics task that typically involves transferring the pose of a reference avatar to a (stylized) three-dimensional character. Since three-dimensional characters are created by professional artists through imagination and exaggeration, and therefore, unlike human or animal avatars, have distinct shape and features, matching the pose of a three-dimensional character to that of a reference avatar generally requires manually creating shape information for the three-dimensional character that is required for pose transfer. The present disclosure provides for the automated transfer of a reference pose to a three-dimensional character, based specifically on a learned shape code for the three-dimensional character.
-
公开(公告)号：US11880927B2
公开(公告)日：2024-01-23
申请号：US18320446
申请日：2023-05-19
Applicant: NVIDIA Corporation
Inventor： Xueting Li , Sifei Liu , Kihwan Kim , Shalini De Mello , Jan Kautz
CPC classification number: G06T15/04 , G06T7/579 , G06T7/70 , G06T15/20 , G06T17/20 , G06T2207/10016 , G06T2207/20084 , G06T2207/30244
Abstract: A three-dimensional (3D) object reconstruction neural network system learns to predict a 3D shape representation of an object from a video that includes the object. The 3D reconstruction technique may be used for content creation, such as generation of 3D characters for games, movies, and 3D printing. When 3D characters are generated from video, the content may also include motion of the character, as predicted based on the video. The 3D object construction technique exploits temporal consistency to reconstruct a dynamic 3D representation of the object from an unlabeled video. Specifically, an object in a video has a consistent shape and consistent texture across multiple frames. Texture, base shape, and part correspondence invariance constraints may be applied to fine-tune the neural network system. The reconstruction technique generalizes well—particularly for non-rigid objects.
-
公开(公告)号：US20220270318A1
公开(公告)日：2022-08-25
申请号：US17734244
申请日：2022-05-02
Applicant: NVIDIA Corporation
Inventor： Xueting Li , Sifei Liu , Kihwan Kim , Shalini De Mello , Jan Kautz
Abstract: A three-dimensional (3D) object reconstruction neural network system learns to predict a 3D shape representation of an object from a video that includes the object. The 3D reconstruction technique may be used for content creation, such as generation of 3D characters for games, movies, and 3D printing. When 3D characters are generated from video, the content may also include motion of the character, as predicted based on the video. The 3D object construction technique exploits temporal consistency to reconstruct a dynamic 3D representation of the object from an unlabeled video. Specifically, an object in a video has a consistent shape and consistent texture across multiple frames. Texture, base shape, and part correspondence invariance constraints may be applied to fine-tune the neural network system. The reconstruction technique generalizes well—particularly for non-rigid objects.
-
-
-
-
-
-
-
-
-
Search Results
14
records
(took 0.013 seconds)
