Invention Grant
- Patent Title: Machine learning based controllable animation of still images
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Application No.: US17856362Application Date: 2022-07-01
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Publication No.: US12282992B2Publication Date: 2025-04-22
- Inventor: Kuldeep Kulkarni , Aniruddha Mahapatra
- Applicant: ADOBE INC.
- Applicant Address: US CA San Jose
- Assignee: ADOBE INC.
- Current Assignee: ADOBE INC.
- Current Assignee Address: US CA San Jose
- Agency: Shook, Hardy & Bacon L.L.P.
- Main IPC: G06T13/80
- IPC: G06T13/80 ; G06T3/18 ; G06T7/215

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.
Public/Granted literature
- US20240005587A1 MACHINE LEARNING BASED CONTROLLABLE ANIMATION OF STILL IMAGES Public/Granted day:2024-01-04
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