公开(公告)号：US20250095172A1

公开(公告)日：2025-03-20

申请号：US18369958

申请日：2023-09-19

Applicant: Adobe Inc.

Inventor： Sanjeev Muralikrishnan ,  Chun-Hao Huang ,  Duygu Ceylan Aksit ,  Niloy J. Mitra

IPC: G06T7/38 ,  G06T7/73 ,  G06T17/10

Abstract: In some examples, a computing system access a set of registered three-dimensional (3D) digital shapes. The set of registered 3D digital shapes are registered to a shape template. The computing system determines a linear model for an estimate of the shape space using a first subset of the set of registered 3D digital shapes. The computing system then determines a nonlinear deformation model for the shape space using a second subset of the set of registered 3D digital shapes. An unregistered shape can be registered to the shape space using the linear model and the nonlinear deformation model. The registration can be added to the set of registered 3D digital shapes to update the estimate of the shape space if a shape distance between the registration and the unregistered shape is below a threshold value.

公开(公告)号：US20250111866A1

公开(公告)日：2025-04-03

申请号：US18479626

申请日：2023-10-02

Applicant: Adobe Inc.

Inventor： Duygu Ceylan Aksit ,  Niloy Mitra ,  Chun-Hao Huang

IPC: G11B27/031 ,  G06T7/50

Abstract: Embodiments are disclosed for editing video using image diffusion. The method may include receiving an input video depicting a target and a prompt including an edit to be made to the target. A keyframe associated with the input video is then identified. The keyframe is edited, using a generative neural network, based on the prompt to generate an edited keyframe. A subsequent frame of the input video is edited using the generative neural network, based on the prompt, features of the edited keyframe, and features of an intervening frame to generate an edited output video.