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Introduction to Point Cloud (3D Deep Learning and PointNet) [Intermediate]

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by Super AI Engineer Course
Course level: Intermediate
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Categories Image Processing
Duration 04h 03m 06s
Total Enrolled 23063
Last Update November 1, 2021

Description

อาจารย์ผู้สอน

ดร.เชิดศักดิ์ กิ่งก้าน

ศูนย์เทคโนโลยีอิเล็กทรอนิกส์และคอมพิวเตอร์แห่งชาติ

*** วิชานี้สงวนสิทธิ์เฉพาะผู้สมัครเข้าร่วมโครงการ Super AI Engineer เท่านั้น

สำหรับผู้ที่สมัครโครงการ Super AI Engineer สามารถ Start Course ได้ในวันที่ 10 ตุลาคม 2564 เป็นต้นไป

What Will I Learn?

องค์ความรู้เชิงลึกด้าน Image Processing

Topics for this course

22 Lessons04h 03m 06s

Introduction 3D Deep Learning

EP.1 – Introduction 3D Deep Learning and voxel-based00:04:16

EP.2 – Point-based and Graph-based00:07:54

Deep Learning to PointNet

Examples from Published

Library Installation and Data Processing

Model Deployment

Dynamic Graph CNN for Learning on Point Clouds Model

Message Passing Networks

Visualization

Attention Mechanism

About the instructors

Super AI Engineer Course

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บุคคลทั่วไปที่สนใจหรือผู้ที่ต้องการทบทวนองค์ความรู้ด้านปัญญาประดิษฐ์

Introduction to Point Cloud (3D Deep Learning and PointNet) [Intermediate]

Description

What Will I Learn?

Topics for this course

Introduction 3D Deep Learning

EP.1 – Introduction 3D Deep Learning and voxel-based00:04:16

EP.2 – Point-based and Graph-based00:07:54

Deep Learning to PointNet

EP.3 – Point Net – Introduction and Input00:11:07

EP.4 – Point Net – Embedding Space, OOS, and Result00:10:37

EP.5 – Q&A – Point Net00:12:56

EP.6 – Hands On00:12:52

Examples from Published

EP.7 – Paper Generating Mesh-based Shapes From learned latent of Point Clouds with VAE-GAN00:20:48

EP.8 – Paper Point Attention Network for Gesture Recognition Using Point Cloud Data00:20:06

EP.9 – Q&A – Paper00:16:33

EP.10 – Q&A – Gather, Scatter, and Mesh base00:05:47

EP.11 – Q&A – Keypoint 3D and VAE-GAN00:11:32

Library Installation and Data Processing

EP.12 – Library Installation and Data Processing00:11:27

EP.13 – Pytorch -geometric Concept, Data Loader and Model Function00:04:59

EP.14 – Create Dataset Using Pytorch00:14:36

EP.15 – Q and A00:04:03

EP.16 – Summary Create Dataset00:09:08

Model Deployment

EP.17 – MLP Lalyer and DynamicEdgeConv00:06:14

EP.18 – Epoch, Features, Normalization, KNN, and Deploy Model00:13:30

Dynamic Graph CNN for Learning on Point Clouds Model

EP.19 – Paper Dynamic Graph CNN for Learning on Point Clouds00:05:42

Message Passing Networks

EP.20 – Message Passing Networks00:12:32

Visualization

EP.21 – Visualization00:06:59

Attention Mechanism

EP.22 – Attention Mechanism00:11:56

About the instructors

Super AI Engineer Course

Student Feedback

Tags

Target Audience

Introduction to Point Cloud (3D Deep Learning and PointNet) [Intermediate]

Description

What Will I Learn?

Topics for this course

Introduction 3D Deep Learning

EP.1 – Introduction 3D Deep Learning and voxel-based00:04:16

EP.2 – Point-based and Graph-based00:07:54

Deep Learning to PointNet

EP.3 – Point Net – Introduction and Input00:11:07

EP.4 – Point Net – Embedding Space, OOS, and Result00:10:37

EP.5 – Q&A – Point Net00:12:56

EP.6 – Hands On00:12:52

Examples from Published

EP.7 – Paper Generating Mesh-based Shapes From learned latent of Point Clouds with VAE-GAN00:20:48

EP.8 – Paper Point Attention Network for Gesture Recognition Using Point Cloud Data00:20:06

EP.9 – Q&A – Paper00:16:33

EP.10 – Q&A – Gather, Scatter, and Mesh base00:05:47

EP.11 – Q&A – Keypoint 3D and VAE-GAN00:11:32

Library Installation and Data Processing

EP.12 – Library Installation and Data Processing00:11:27

EP.13 – Pytorch -geometric Concept, Data Loader and Model Function00:04:59

EP.14 – Create Dataset Using Pytorch00:14:36

EP.15 – Q and A00:04:03

EP.16 – Summary Create Dataset00:09:08

Model Deployment

EP.17 – MLP Lalyer and DynamicEdgeConv00:06:14

EP.18 – Epoch, Features, Normalization, KNN, and Deploy Model00:13:30

Dynamic Graph CNN for Learning on Point Clouds Model

EP.19 – Paper Dynamic Graph CNN for Learning on Point Clouds00:05:42

Message Passing Networks

EP.20 – Message Passing Networks00:12:32

Visualization

EP.21 – Visualization00:06:59

Attention Mechanism

EP.22 – Attention Mechanism00:11:56

About the instructors

Super AI Engineer Course

Student Feedback

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Tags

Target Audience

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