-
公开(公告)号：US11914951B2
公开(公告)日：2024-02-27
申请号：US18170125
申请日：2023-02-16
Applicant: Adobe Inc.
Inventor： Vinay Aggarwal , Vishwa Vinay , Rizurekh Saha , Prabhat Mahapatra , Niyati Himanshu Chhaya , Harshit Agrawal , Chloe McConnell , Bhanu Prakash Reddy Guda , Balaji Vasan Srinivasan
IPC: G06F40/186 , G06F40/109 , G06F40/30 , G06N20/00 , G06F18/2411
CPC classification number: G06F40/186 , G06F18/2411 , G06F40/109 , G06F40/30 , G06N20/00
Abstract: Techniques for template generation from image content include extracting information associated with an input image. The information comprises: 1) layout information indicating positions of content corresponding to a content type of a plurality of content types within the input image; and 2) text attributes indicating at least a font of text included in the input image. A user-editable template having the characteristics of the input image is generated based on the layout information and the text attributes.
-
公开(公告)号：US20230290146A1
公开(公告)日：2023-09-14
申请号：US17691526
申请日：2022-03-10
Applicant: Adobe Inc.
Inventor： Niyati Himanshu Chhaya , Tripti Shukla , Jeevana Kruthi Karnuthala , Bhanu Prakash Reddy Guda , Ayudh Saxena , Abhinav Bohra , Abhilasha Sancheti , Aanisha Bhattacharyya
IPC: G06V20/40 , G06F16/73 , G06N20/00 , G06F40/166 , G06V10/86
Abstract: Techniques are described that support automated generation of a digital document from digital videos using machine learning. The digital document includes textual components that describe a sequence of entity and action descriptions from the digital video. These techniques are usable to generate a single digital document based on a plurality of digital videos as well as incorporate user-specified constraints in the generation of the digital document.
-
公开(公告)号：US20220253630A1
公开(公告)日：2022-08-11
申请号：US17170307
申请日：2021-02-08
Applicant: ADOBE INC.
Inventor： Sumit Shekhar , Bhanu Prakash Reddy Guda , Ashutosh Chaubey , Ishan Jindal , Avneet Jain
Abstract: Systems and methods for training an object detection network are described. Embodiments train an object detection network using a labeled training set, wherein each element of the labeled training set includes an image and ground truth labels for object instances in the image, predict annotation data for a candidate set of unlabeled data using the object detection network, select a sample image from the candidate set using a policy network, generate a labeled sample based on the selected sample image and the annotation data, wherein the labeled sample includes labels for a plurality of object instances in the sample image, and perform additional training on the object detection network based at least in part on the labeled sample.
-
公开(公告)号：US20220019909A1
公开(公告)日：2022-01-20
申请号：US16928888
申请日：2020-07-14
Applicant: ADOBE INC.
Inventor： Samarth Aggarwal , Rohin Garg , Bhanu Prakash Reddy Guda , Abhilasha Sancheti , Iftikhar Ahamath Burhanuddin
Abstract: Methods, systems, and computer storage media for providing command recommendations for an analysis-goal, using analytics system operations in an analytics systems. In operation, an analytics client is configured to provide an analytics interface for receiving a selection of analysis-goal information that corresponds to an analysis-goal model. A goal engine selects an analysis-goal based on the analysis-goal information. A command engine is configured to use the analysis-goal and goal-driven models to predict probable commands for the analysis goal. The command engine also selects a next command recommendation from the probable commands. The command engine generates additional command recommendation data based on a loss function fine tuner. The additional command recommendation data can include a goal orientation score that quantifies a degree to which a command aligns with the analysis-goal. The next command recommendation and additional command recommendation output data are communicated and caused to be displayed on the analytics interface.
-
-
-
Search Results
14
records
(took 0.027 seconds)
