Archives for face recognition

23 Jun

FACE RECOGNITION SYSTEM USING DEEPFACE(With Python Codes)

image-23777
image-23777

Recognition of the face as an identity is a critical aspect in today’s world. Facial identification and recognition find its use in many real-life contexts, whether your identity card, passport, or any other credential of significant importance. It has become quite a popular tool these days to authenticate the identity of an individual. This technology…

The post FACE RECOGNITION SYSTEM USING DEEPFACE(With Python Codes) appeared first on Analytics India Magazine.

10 Feb

Hands-on Python Guide to Style-based Age Manipulation (SAM) Technique

image-19912
image-19912

Introduction Style-based Age Manipulation (SAM) is a method used to perform fine-grained age transformation in digital image processing and computer vision tasks using a single facial image as an input. It was introduced by Yuval Alalu, Or Patashnik and Daneil Cohen-Or of Tel-Aviv University in February 2021 (research paper). This article gives an overview of…

The post Hands-on Python Guide to Style-based Age Manipulation (SAM) Technique appeared first on Analytics India Magazine.

21 Jan

Guide Towards Fast, Accurate, and Stable 3D Dense Face Alignment(3DDFA-V2) Framework

image-19365
image-19365

3D dense face alignment(3DDFA) is a trending technique for many face tasks, For example, object recognition, animation, tracking, image restoration, and many more. For now, most of the studies in 3DDFA are divided into two categories: 3D Morphable Model(3DMM) parameter regression, and Dense vertices regression. Now Existing method of 3D dense face alignment only focuses…

The post Guide Towards Fast, Accurate, and Stable 3D Dense Face Alignment(3DDFA-V2) Framework appeared first on Analytics India Magazine.

21 Jan

Guide Towards Fast, Accurate, and Stable 3D Dense Face Alignment(3DDFA-V2) Framework

image-19366
image-19366

3D dense face alignment(3DDFA) is a trending technique for many face tasks, For example, object recognition, animation, tracking, image restoration, and many more. For now, most of the studies in 3DDFA are divided into two categories: 3D Morphable Model(3DMM) parameter regression, and Dense vertices regression. Now Existing method of 3D dense face alignment only focuses…

The post Guide Towards Fast, Accurate, and Stable 3D Dense Face Alignment(3DDFA-V2) Framework appeared first on Analytics India Magazine.