公开(公告)号：US20240005587A1

公开(公告)日：2024-01-04

申请号：US17856362

申请日：2022-07-01

Applicant: ADOBE INC.

Inventor： Kuldeep KULKARNI ,  Aniruddha MAHAPATRA

IPC: G06T13/80 ,  G06T7/215 ,  G06T3/00

CPC classification number: G06T13/80 ,  G06T7/215 ,  G06T2207/20084 ,  G06T2207/20081 ,  G06T2207/10016 ,  G06T3/0093

Abstract: Systems and methods for machine learning based controllable animation of still images is provided. In one embodiment, a still image including a fluid element is obtained. Using a flow refinement machine learning model, a refined dense optical flow is generated for the still image based on a selection mask that includes the fluid element and a dense optical flow generated from a motion hint that indicates a direction of animation. The refined dense optical flow indicates a pattern of apparent motion for the at least one fluid element. Thereafter, a plurality of video frames is generated by projecting a plurality of pixels of the still image using the refined dense optical flow.

公开(公告)号：US20240012849A1

公开(公告)日：2024-01-11

申请号：US17862258

申请日：2022-07-11

Applicant: Adobe Inc.

Inventor： Praneetha VADDAMANU ,  Nihal JAIN ,  Paridhi MAHESHWARI ,  Kuldeep KULKARNI ,  Vishwa VINAY ,  Balaji Vasan SRINIVASAN ,  Niyati CHHAYA ,  Harshit AGRAWAL ,  Prabhat MAHAPATRA ,  Rizurekh SAHA

IPC: G06F16/532 ,  G06V10/74 ,  G06V10/56 ,  G06V10/82 ,  G06V20/30 ,  G06V10/774 ,  G06F16/535

CPC classification number: G06F16/532 ,  G06V10/761 ,  G06V10/56 ,  G06V10/82 ,  G06V20/30 ,  G06V10/774 ,  G06F16/535

Abstract: Embodiments are disclosed for multichannel content recommendation. The method may include receiving an input collection comprising a plurality of images. The method may include extracting a set of feature channels from each of the images. The method may include generating, by a trained machine learning model, an intent channel of the input collection from the set of feature channels. The method may include retrieving, from a content library, a plurality of search result images that include a channel that matches the intent channel. The method may include generating a recommended set of images based on the intent channel and the set of feature channels.

公开(公告)号：US20240135197A1

公开(公告)日：2024-04-25

申请号：US17962962

申请日：2022-10-10

Applicant: Adobe Inc.

Inventor： Vishwa VINAY ,  Tirupati Saketh CHANDRA ,  Rishi AGARWAL ,  Kuldeep KULKARNI ,  Hiransh GUPTA ,  Aniruddha MAHAPATRA ,  Vaidehi Ramesh PATIL

IPC: G06N5/02

CPC classification number: G06N5/022

Abstract: Embodiments are disclosed for expanding a seed scene using proposals from a generative model of scene graphs. The method may include clustering subgraphs according to respective one or more maximal connected subgraphs of a scene graph. The scene graph includes a plurality of nodes and edges. The method also includes generating a scene sequence for the scene graph based on the clustered subgraphs. A first machine learning model determines a predicted node in response to receiving the scene sequence. A second machine learning model determines a predicted edge in response to receiving the scene sequence and the predicted node. A scene graph is output according to the predicted node and the predicted edge.

公开(公告)号：US20230326088A1

公开(公告)日：2023-10-12

申请号：US17714812

申请日：2022-04-06

Applicant: Adobe Inc.

Inventor： Suryateja BV ,  Sharmila Reddy NANGI ,  Rushil GUPTA ,  Rajat JAISWAL ,  Nikhil KAPOOR ,  Kuldeep KULKARNI

IPC: G06T9/00 ,  G06T3/40 ,  G06N3/08 ,  G06N3/04

CPC classification number: G06T9/002 ,  G06T3/4046 ,  G06N3/08 ,  G06N3/0454

Abstract: Embodiments are disclosed for user-guided variable-rate compression. A method of user-guided variable-rate compression includes receiving a request to compress an image, the request including the image, a corresponding importance data, and a target bitrate, providing the image, the corresponding importance data, and the target bitrate to a compression network, generating, by the compression network, a learned importance map and a representation of the image, and generating, by the compressing network, a compressed representation of the image based on the learned importance map and the representation of the image.

公开(公告)号：US20230121355A1

公开(公告)日：2023-04-20

申请号：US18082386

申请日：2022-12-15

Applicant: Adobe Inc.

Inventor： Balaji Vasan SRINIVASAN ,  Sujith Sai VENNA ,  Kuldeep KULKARNI ,  Durga Prasad MARAM ,  Dasireddy Sai Shritishma REDDY

IPC: G06F16/332 ,  G06F16/35 ,  G06F17/18 ,  G06N3/08 ,  G06V30/148

Abstract: Enhanced techniques and circuitry are presented herein for providing responses to user questions from among digital documentation sources spanning various documentation formats, versions, and types. One example includes a method comprising receiving a user question directed to subject having a documentation corpus, determining a set of passages of the documentation corpus related to the user question, ranking the set of passages according to relevance to the user question, forming semantic clusters comprising sentences extracted from ranked ones of the set of passages according to sentence similarity, and providing a response to the user question based at least on a selected semantic cluster.