公开(公告)号：US20250078401A1

公开(公告)日：2025-03-06

申请号：US18242648

申请日：2023-09-06

Applicant: Adobe Inc.

Inventor： Mainak Biswas ,  Nishtha Behal ,  Anubhav Jain

IPC: G06T17/00 ,  G06T3/40 ,  G06T7/20 ,  G06T7/70 ,  G06V10/24

Abstract: A system accesses, during a camera scan of a 3D physical object, video feed data of a user computing device including a plurality of frames. The system generates camera scan data including a set of 2D images of the physical object generated from a subset of the plurality of frames. Generating the camera scan data can include, responsive to determining that a translation between a previous frame and a current frame is greater than a threshold, including the current frame in the camera scan data. Generating the camera scan data can include excluding the current frame from the camera scan data responsive to determining an undesired camera movement type associated with the current frame. Generating the camera scan data can include indicating, in a surface coverage preview model, points of the 3D physical object included in at least a predefined number of consecutive frames of the subset of frames.

公开(公告)号：US20230127525A1

公开(公告)日：2023-04-27

申请号：US17512264

申请日：2021-10-27

Applicant: Adobe Inc.

Inventor： Nishant Rai ,  Shivam Mishra ,  Nitesh Jain ,  Nikhil Gupta ,  Anubhav Jain

IPC: G06N3/04

Abstract: The present disclosure describes methods, systems, and non-transitory computer-readable media for implementing a machine learning framework to generate a recommend digital assets from a digital image. For example, in one or more embodiments, the disclosed systems utilize a machine learning model to detect a shape, color, pattern, or other digital asset type from a digital image and then extract (and further modify) the detected asset type to create various different digital assets as recommendations. In some cases, the disclosed system utilizes the machine learning model to determine one or more digital asset classes associated with the digital image, generate preprocessed digital assets from the digital image for those digital asset classes, and generate production-ready digital assets from the preprocessed digital assets. Further, in some instances, the disclosed systems provide one or more of the digital assets via recommendations based on asset scores determined via the generation process.

公开(公告)号：US10783170B2

公开(公告)日：2020-09-22

申请号：US15241148

申请日：2016-08-19

Applicant: Adobe Inc.

Inventor： Ashish Sharma ,  Anubhav Jain

IPC: G06F16/29 ,  G06T7/70

Abstract: Techniques are disclosed for assigning a geographical location to a photograph of a landscape. A geographic location tag is calculated from raw sensor data and a three-dimensional terrain map that corresponds to the landscape in the photograph. One technique includes calculating a two-dimensional ideal view projection of a camera used to take the landscape photograph based at least in part on a geographic location of the camera when the landscape photograph was taken and a field of view of the camera when the landscape photograph was taken. At least one of the topographical features visible from the camera based on the two-dimensional ideal view projection is selected from a three-dimensional terrain map representing a plurality of topographical features within a geographic region. At least one geographic location tag representing at least one of the selected topographical features is assigned to the landscape photograph.