Lesson List
Introduction 3D Deep Learning
EP.1 – Introduction 3D Deep Learning and voxel-based
00:04:16
EP.2 – Point-based and Graph-based
00:07:54
Deep Learning to PointNet
EP.3 – Point Net – Introduction and Input
00:11:07
EP.4 – Point Net – Embedding Space, OOS, and Result
00:10:37
EP.5 – Q&A – Point Net
00:12:56
EP.6 – Hands On
00:12:52
Examples from Published
EP.7 – Paper Generating Mesh-based Shapes From learned latent of Point Clouds with VAE-GAN
00:20:48
EP.8 – Paper Point Attention Network for Gesture Recognition Using Point Cloud Data
00:20:06
EP.9 – Q&A – Paper
00:16:33
EP.10 – Q&A – Gather, Scatter, and Mesh base
00:05:47
EP.11 – Q&A – Keypoint 3D and VAE-GAN
00:11:32
Library Installation and Data Processing
EP.12 – Library Installation and Data Processing
00:11:27
EP.13 – Pytorch -geometric Concept, Data Loader and Model Function
00:04:59
EP.14 – Create Dataset Using Pytorch
00:14:36
EP.15 – Q and A
00:04:03
EP.16 – Summary Create Dataset
00:09:08
Model Deployment
EP.17 – MLP Lalyer and DynamicEdgeConv
00:06:14
EP.18 – Epoch, Features, Normalization, KNN, and Deploy Model
00:13:30
Dynamic Graph CNN for Learning on Point Clouds Model
EP.19 – Paper Dynamic Graph CNN for Learning on Point Clouds
00:05:42
Message Passing Networks
EP.20 – Message Passing Networks
00:12:32
Visualization
EP.21 – Visualization
00:06:59
Attention Mechanism
EP.22 – Attention Mechanism
00:11:56
Go to Course Home
EP.1 – Introduction 3D Deep Learning and voxel-based
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