公开(公告)号：US20250061660A1

公开(公告)日：2025-02-20

申请号：US18451961

申请日：2023-08-18

Applicant: ADOBE INC.

Inventor： Ta-Ying Cheng ,  Matheus Gadelha ,  Soren Pirk ,  Radomir Mech ,  Thibault Groueix

IPC: G06T17/20 ,  G06V10/46 ,  G06V10/762

Abstract: Systems and methods for extracting 3D shapes from unstructured and unannotated datasets are described. Embodiments are configured to obtain a first image and a second image, where the first image depicts an object and the second image includes a corresponding object of a same object category as the object. Embodiments are further configured to generate, using an image encoder, image features for portions of the first image and for portions of the second image; identify a keypoint correspondence between a first keypoint in the first image and a second keypoint in the second image by clustering the image features corresponding to the portions of the first image and the portions of the second image; and generate, using an occupancy network, a 3D model of the object based on the keypoint correspondence.

公开(公告)号：US20250117995A1

公开(公告)日：2025-04-10

申请号：US18481719

申请日：2023-10-05

Applicant: ADOBE INC.

Inventor： Yijun Li ,  Matheus Abrantes Gadelha ,  Krishna Kumar Singh ,  Soren Pirk

IPC: G06T11/60 ,  G06T5/00 ,  G06T7/50 ,  G06V10/26

Abstract: Methods, non-transitory computer readable media, apparatuses, and systems for image and depth map generation include receiving a prompt and encoding the prompt to obtain a guidance embedding. A machine learning model then generates an image and a depth map corresponding to the image based on the guidance embedding. The image and the depth map are each generated based on the guidance embedding.