Invention Grant
- Patent Title: Semi-supervised learning for landmark localization
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Application No.: US16006709Application Date: 2018-06-12
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Publication No.: US10783393B2Publication Date: 2020-09-22
- Inventor: Pavlo Molchanov , Stephen Walter Tyree , Jan Kautz , Sina Honari
- Applicant: NVIDIA Corporation
- Applicant Address: US CA Santa Clara
- Assignee: NVIDIA Corporation
- Current Assignee: NVIDIA Corporation
- Current Assignee Address: US CA Santa Clara
- Agency: Leydig, Voit & Mayer, Ltd.
- Main IPC: G06K9/00
- IPC: G06K9/00 ; G06K9/62 ; G06K9/46 ; G06N3/08 ; G06K9/66 ; G06N3/04

Abstract:
A method, computer readable medium, and system are disclosed for sequential multi-tasking to generate coordinates of landmarks within images. The landmark locations may be identified on an image of a human face and used for emotion recognition, face identity verification, eye gaze tracking, pose estimation, etc. A neural network model processes input image data to generate pixel-level likelihood estimates for landmarks in the input image data and a soft-argmax function computes predicted coordinates of each landmark based on the pixel-level likelihood estimates.
Public/Granted literature
- US20180365532A1 SEMI-SUPERVISED LEARNING FOR LANDMARK LOCALIZATION Public/Granted day:2018-12-20
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