公开(公告)号：US20240020915A1

公开(公告)日：2024-01-18

申请号：US18353213

申请日：2023-07-17

Applicant: Google LLC

Inventor： Yinda Zhang ,  Feitong Tan ,  Sean Ryan Francesco Fanello ,  Abhimitra Meka ,  Sergio Orts Escolano ,  Danhang Tang ,  Rohit Kumar Pandey ,  Jonathan James Taylor

IPC: G06T15/80 ,  G06T15/08

CPC classification number: G06T15/80 ,  G06T15/08

Abstract: Techniques include introducing a neural generator configured to produce novel faces that can be rendered at free camera viewpoints (e.g., at any angle with respect to the camera) and relit under an arbitrary high dynamic range (HDR) light map. A neural implicit intrinsic field takes a randomly sampled latent vector as input and produces as output per-point albedo, volume density, and reflectance properties for any queried 3D location. These outputs are aggregated via a volumetric rendering to produce low resolution albedo, diffuse shading, specular shading, and neural feature maps. The low resolution maps are then upsampled to produce high resolution maps and input into a neural renderer to produce relit images.

公开(公告)号：US20240290025A1

公开(公告)日：2024-08-29

申请号：US18588948

申请日：2024-02-27

Applicant: GOOGLE LLC

Inventor： Yinda Zhang ,  Sean Ryan Francesco Fanello ,  Ziqian Bai ,  Feitong Tan ,  Zeng Huang ,  Kripasindhu Sarkar ,  Danhang Tang ,  Di Qiu ,  Abhimitra Meka ,  Ruofei Du ,  Mingsong Dou ,  Sergio Orts Escolano ,  Rohit Kumar Pandey ,  Thabo Beeler

IPC: G06T13/40 ,  G06T7/90 ,  G06T17/20 ,  G06V10/44

CPC classification number: G06T13/40 ,  G06T7/90 ,  G06T17/20 ,  G06V10/44 ,  G06T2207/10024 ,  G06T2207/20084

Abstract: A method comprises receiving a first sequence of images of a portion of a user, the first sequence of images being monocular images; generating an avatar based on the first sequence of images, the avatar being based on a model including a feature vector associated with a vertex; receiving a second sequence of images of the portion of the user; and based on the second sequence of images, modifying the avatar with a displacement of the vertex to represent a gesture of the avatar.

公开(公告)号：US20240212325A1

公开(公告)日：2024-06-27

申请号：US18596822

申请日：2024-03-06

Applicant: Google LLC

Inventor： Yinda Zhang ,  Feitong Tan ,  Danhang Tang ,  Mingsong Dou ,  Kaiwen Guo ,  Sean Ryan Francesco Fanello ,  Sofien Bouaziz ,  Cem Keskin ,  Ruofei Du ,  Rohit Kumar Pandey ,  Deqing Sun

IPC: G06V10/771 ,  G06T7/70 ,  G06T17/00 ,  G06V10/44 ,  G06V10/75

CPC classification number: G06V10/771 ,  G06T7/70 ,  G06T17/00 ,  G06V10/44 ,  G06V10/751 ,  G06T2207/20081 ,  G06T2207/20084

Abstract: Systems and methods for training models to predict dense correspondences across images such as human images. A model may be trained using synthetic training data created from one or more 3D computer models of a subject. In addition, one or more geodesic distances derived from the surfaces of one or more of the 3D models may be used to generate one or more loss values, which may in turn be used in modifying the model's parameters during training.

公开(公告)号：US11954899B2

公开(公告)日：2024-04-09

申请号：US18274371

申请日：2021-03-11

Applicant: Google LLC

Inventor： Yinda Zhang ,  Feitong Tan ,  Danhang Tang ,  Mingsong Dou ,  Kaiwen Guo ,  Sean Ryan Francesco Fanello ,  Sofien Bouaziz ,  Cem Keskin ,  Ruofei Du ,  Rohit Kumar Pandey ,  Deqing Sun

IPC: G06V10/771 ,  G06T7/70 ,  G06T17/00 ,  G06V10/44 ,  G06V10/75

CPC classification number: G06V10/771 ,  G06T7/70 ,  G06T17/00 ,  G06V10/44 ,  G06V10/751 ,  G06T2207/20081 ,  G06T2207/20084

Abstract: Systems and methods for training models to predict dense correspondences across images such as human images. A model may be trained using synthetic training data created from one or more 3D computer models of a subject. In addition, one or more geodesic distances derived from the surfaces of one or more of the 3D models may be used to generate one or more loss values, which may in turn be used in modifying the model's parameters during training.

公开(公告)号：US20240046618A1

公开(公告)日：2024-02-08

申请号：US18274371

申请日：2021-03-11

Applicant: Google LLC

Inventor： Yinda Zhang ,  Feitong Tan ,  Danhang Tang ,  Mingsong Dou ,  Kaiwen Guo ,  Sean Ryan Francesco Fanello ,  Sofien Bouaziz ,  Cem Keskin ,  Ruofei Du ,  Rohit Kumar Pandey ,  Deqing Sun

IPC: G06V10/771 ,  G06T17/00 ,  G06T7/70 ,  G06V10/44 ,  G06V10/75

CPC classification number: G06V10/771 ,  G06T17/00 ,  G06T7/70 ,  G06V10/44 ,  G06V10/751 ,  G06T2207/20081 ,  G06T2207/20084

Abstract: Systems and methods for training models to predict dense correspondences across images such as human images. A model may be trained using synthetic training data created from one or more 3D computer models of a subject. In addition, one or more geodesic distances derived from the surfaces of one or more of the 3D models may be used to generate one or more loss values, which may in turn be used in modifying the model's parameters during training.