Deep Learning for Visual Computing

Link to the lab part of the course (projects): [github]
Link to the schedule of the current semester: [google docs]

Course Content

Lecture: Syllabus
Syllabus: [Slides]

Lecture: Introduction
Introduction: [Slides] - [youtube] 43 min

Lecture: Linear Algebra Review
Review Linear Algebra: [Slides] - [youtube] 1:17 min

Lecture: Image Classification Problem
Image Classification Problem: [Slides] - [youtube] 28 min

Lecture: Data Structures
Data Structures: [Slides] - [youtube] 25 min

Lecture: Fully Connected Neural Networks
Fully Connected Neural Networks: [Slides] - [youtube] 58 min
Notebook - Fully Connected and Convolutional Layers: [colab]
Demo - Experimenting with Tensorflow: [youtube] 10 min

Lecture: Loss Functions
Loss Functions: [Slides] - [youtube] 47 min

Lecture: Convolution
Convolution: [Slides] - [youtube] 1:12 min

Lecture: Activation Functions
Activation Functions: [Slides] - [youtube] 54 min

Lecture: Network Normalization
Network Normalization: [Slides] - [youtube] 56 min

Lecture: Backpropagation
Backpropagation: [Slides] - [youtube] Part 1: 51 min - [youtube] Part 2: 1:04 min - [youtube] Part 3: 33 min

Lecture: Data Normalization
Data Normalization: [Slides] - [youtube] 25 min

Lecture: Network Initialization
Network Initialization: [Slides] - [youtube] 51 min

Lecture: Network Regularization
Network Regularization: [Slides] - [youtube] 40 min
Notebook - Dropout: [colab]

Lecture: Data Augmentation
Data Augmentation: [Slides] - [youtube] 44 min
Notebook - Data Augmentation: [colab]

Lecture: Optimization
Optimization: [Slides] - [youtube] Part 1: 17 min - [youtube] Part 2: 1:14 min - [youtube] Part 3: 43 min

Lecture: Classification Architectures
Classification Architectures: [Slides] - [youtube] Part 1 1:07 min - [youtube] Part 2 1:45 min
Notebook - Print Classification Architecture: [colab]
Lecture: Training Neural Networks
Training Neural Networks (Justin Johnson): [Slides] - [youtube] 1:19 min

Lecture: Texture Synthesis and Style Transfer
Texture Synthesis: [Slides] - [youtube] 50 min
Style Transfer: [Slides] - [youtube] 1:14 min

Lecture: Visualization
Visualization: [Slides] - [youtube] 1:04 min
Notebook - Wandb: [colab] link on the top right
3D Network Visualization (Denis Dmitriev): [youtube] 2 min
Deep Visualization Toolbox (Yason Yosinski): [youtube] 3 min
Network Analysis: [Slides] - [youtube] Part 1 19 min - [youtube] Part 2 16 min - [youtube] Part 3 27 min

Lecture: Attention
Attention (Justin Johnson): [Slides] - [youtube] 1:11 min

Lecture: Object Detection and Segmentation
Object Detection (Justin Johnson): [Slides]
Object Detectors (Justin Johnson): [Slides]
Image Segmentation (Justin Johnson): [Slides]
Object Detection (Justin Johnson 2019): [youtube] 1:21 min
Object Detection and Segmentation (Justin Johnson 2019): [youtube] 1:10 min
Notebook - Upsampling Functions: [colab]

Lecture: GANs
GANs: [Slides] -
[youtube] Part 1 20 min
[youtube] Part 2 24 min
[youtube] Part 3 24 min
[youtube] Part 4 33 min
[youtube] Part 5 43 min

Lecture: Transformer Examples in Computer Vision
BERT (Shusen Wang): [youtube] 15 min
Vision Transformer (Shusen Wang): [youtube] 14 min
DETR (Yannic Kilcher): [youtube]
Vision Transformer (Justin Johnson): [Slides]

Lecture: Point Clouds
Point Clouds: [Slides] -
[youtube] Part 1 17 min
[youtube] Part 2 27 min
[youtube] Part 3 50 min
[youtube] Part 3 21 min

Lecture: Neural Architecture Search
Neural Architecture Search: [Slides] - [youtube] 37 min

Lecture: Information Theory Review
Information Theory Review: [Slides]

Lecture: Recurrent Neural Networks
Recurrent Neural Networks / LSTM (Justin Johnson): [Slides]
Recurrent Neural Networks / LSTM (Justin Johnson): [youtube] 1:13 min

Lecture: Videos
Videos (Justin Johnson): [Slides]

Lecture: Self-Supervised Learning
Self-Supervised Learning (Justin Johnson): [Slides]

Lecture: 3D Vision
3D Vision (Justin Johnson): [Slides]

Lecture: Diffusion
Diffusion: [Tutorial] Includes Slides
[youtube] 3:46 min

Lecture: Career Advice
There is some overlap
Building a career in machine learning (Andrew Ng): [youtube] 1h
Career advice / reading papers (Andrew Ng): [youtube] 1:04 min

Lecture: TBD
XXX: [Slides]