DEEP MULTI-TASK LEARNING FRAMEWORK FOR FACE DETECTION, LANDMARK LOCALIZATION, POSE ESTIMATION, AND GENDER RECOGNITION

Patent №

US 10,860,837

Granted

2020-12-08

Filed 2018

Owner

UNIVERSITY OF MARYLAND, COLLEGE PARK

Lab

AI components

4

ml · vision · kr · hardware

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

15746237

Various image processing may benefit from the application deep convolutional neural networks. For example, a deep multi-task learning framework may assist face detection, for example when combined with landmark localization, pose estimation, and gender recognition. An apparatus can include a first module of at least three modules configured to generate class independent region proposals to provide a region. The apparatus can also include a second module of the at least three modules configured to classify the region as face or non-face using a multi-task analysis. The apparatus can further include a third module configured to perform post-processing on the classified region.

Machine learningVisionKnowledge representationAI hardwareG06V 40/165G06F 18/24G06V 40/171G06V 10/454G06V 10/993

AI classification

Vision1.00
Machine learning1.00
AI hardware1.00
Knowledge representation0.69
Planning0.07
Natural language0.04
Evolutionary computation0.01
Speech0.00

Ownership

UNIVERSITY OF MARYLAND, COLLEGE PARK

assignment · 542770165

Assignors

CASTILLO, CARLOS, CHELLAPPA, RAMALINGAM, PATEL, VISHAL, RANJAN, RAJEEV

On an employer assignment, the assignors are typically the inventors.

From the same owner

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