You're reading from 3D Deep Learning with Python

Product typeBook

Published inOct 2022

PublisherPackt

ISBN-139781803247823

Edition1st Edition

Concepts

Computer Vision

Authors (3):

Xudong Ma

Vishakh Hegde

Lilit Yolyan

View More author details

Estimating 3D human pose and shape using SMPLify

In the previous section, you explored the SMPL model and used it to generate a 3D human body with a random shape and pose. It is natural to wonder whether it is possible to use the SMPL model to fit a 3D human body onto a person in a 2D image. This has multiple practical applications, such as understanding human actions or creating animations from 2D videos. This is indeed possible, and in this chapter, we are going to explore this idea in more detail.

Imagine that you are given a single RGB image of a person without any information about body pose, camera parameters, or shape parameters. Our goal is to deduce the 3D shape and pose from just this single image. Estimating the 3D shape from a 2D image is not always error-free. It is a challenging problem because of the complexity of the human body, articulation, occlusion, clothing, lighting, and the inherent ambiguity in inferring 3D from 2D (because multiple 3D poses can have the...

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3D Deep Learning with Python

Published in: Oct 2022Publisher: PacktISBN-13: 9781803247823

Authors (3)

Xudong Ma

Xudong Ma is a Staff Machine Learning engineer with Grabango Inc. at Berkeley California. He was a Senior Machine Learning Engineer at Facebook(Meta) Oculus and worked closely with the 3D PyTorch Team on 3D facial tracking projects. He has many years of experience working on computer vision, machine learning and deep learning. He holds a Ph.D. in Electrical and Computer Engineering.
Read more about Xudong Ma

Vishakh Hegde

Vishakh Hegde is a Machine Learning and Computer Vision researcher. He has over 7 years of experience in this field during which he has authored multiple well cited research papers and published patents. He holds a masters from Stanford University specializing in applied mathematics and machine learning, and a BS and MS in Physics from IIT Madras. He previously worked at Schlumberger and Matroid. He is a Senior Applied Scientist at Ambient.ai, where he helped build their weapon detection system which is deployed at several Global Fortune 500 companies. He is now leveraging his expertise and passion to solve business challenges to build a technology startup in Silicon Valley. You can learn more about him on his personal website.
Read more about Vishakh Hegde

Lilit Yolyan

Lilit Yolyan is a machine learning researcher working on her Ph.D. at YSU. Her research focuses on building computer vision solutions for smart cities using remote sensing data. She has 5 years of experience in the field of computer vision and has worked on a complex driver safety solution to be deployed by many well-known car manufacturing companies.
Read more about Lilit Yolyan

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Estimating 3D human pose and shape using SMPLify

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