Calendar

Week 1

Jan 11

Lec 1 Course Introduction: 📖 GBC Ch. 1

Project 0 out

Week 2

Jan 16

Lec 2 Image Classification: 📖 231n Image Classification

Jan 17

Dis 1 Intro to Python, Pytorch and Colab

Jan 18

Lec 3 Linear Classifiers: 📖 231n Linear Classification

Project 0 due Project 1 out

Week 3

Jan 23

Lec 4 Regularization + Optimization: 📖 231n Optimization

Quiz 1: 📖 GBC Sec 8.1-8.6

: 📖 Li et al., Visualizing Loss Landscaps

: 📖 Goh, Why Momentum Really Works

Jan 24

Dis 2 Intro to PROPS Dataset: 📖 Chen et al., ProgressLabeller

Jan 25

Lec 5 Neural Networks: 📖 231n Neural Networks

: 📖 GBC Sec 6.1-6.4

: 📖 Nielsen, Universal Approximation

Week 4

Jan 30

Lec 6 Backpropagation: 📖 cs231n Backpropagation

Quiz 2: 📖 GBC Sec 6.5-6.6

: 📖 Olah, Backpropagation

Jan 31

Dis 3 How to Read Research Papers: 📖 Krizhevsky et al., AlexNet

: 📖 Xiang et al., PoseCNN

: 📖 Mildenhall et al., NeRF

Feb 1

Lec 7 Convolutional Neural Networks: 📖 cs231n ConvNets

Quiz 3 Project 1 due Project 2 out: 📖 GBC Ch. 9

: 📖 Araujo et al., Receptive Fields of CNNs

: 📖 Olah et al., Feature Visualization

Week 5

Feb 6

Lec 8 CNN Architectures: 📖 Krizhevsky et al., AlexNet

Quiz 4: 📖 Simonyan and Zisserman, VGG

: 📖 Szegedy et al., GoogLeNet

: 📖 He et al., ResNet

Feb 7

Dis 4 Overview of Final Project Topics: 📖 Vannevar Bush, Science The Endless Frontier

Final Project out Paper Selection Survey Out

Feb 8

Lec 9 Training Neural Networks I: 📖 cs231n Training I

: 📖 Olah et al., Equivariance in Networks

Week 6

Feb 13

Lec 10 Training Neural Networks II: 📖 cs231n Training II

Quiz 5: 📖 Goodfellow et al., Adversarial Examples

Feb 14

Dis 6 How to Present Research Papers

Paper Selection Survey Due

Feb 15

Lec 11 Deep Learning Software

Quiz 6 Project 2 due Project 3 out: 📖 Redmon, Darknet

: 📖 Jia et al., Caffe

: 📖 Abadi et al., TensorFlow

: 📖 Paszke et al., PyTorch

Week 7

Feb 20

Lec 12 Object Detection: 📖 Girshick et al., R-CNN

Quiz 7: 📖 Redmon et al., YOLO

: 📖 Lin et al., FCOS

Feb 21

Dis 7 Prelude to 3D Perception

Feb 22

Lec 13 Object Detectors & Segmentation: 📖 Girshick, Fast R-CNN

Quiz 8: 📖 Ren et al., Faster R-CNN

: 📖 He et al., Mask R-CNN

Spring Break

Feb 27: Break
Feb 28: Break
Feb 29: Break

Week 8; 3D Perception

Mar 5

Lec 14 RGB-D Architectures: 📃 Related Papers

Mar 6

Dis 8 Prelude to Rigid Body Objects

Mar 7

Lec 15 Point Clouds, PointNet, and PointNet++: 📃 Related Papers

Project 3 due Project 4 out

Week 9; Rigid Body Objects

Mar 12

Lec 16 Object Pose, Geometry, SDF, Implicit Surfaces: 📃 Related Papers

Mar 13

Dis 9 Prelude to Object Tracking: 📖 Karpathy, The Unreasonable Effectiveness of RNNs

: 📖 Olah & Carter, Attention and Augmented RNNs

Mar 14

Lec 17 Dense Descriptors, Category-level Representations: 📃 Related Papers

Week 10; Object Tracking

Mar 19

Lec 18 Recurrent Networks, Object Tracking: 📃 Related Papers

Quiz 9

Mar 20

Dis 10 Prelude to Scene-Level Representations

Mar 21

Lec 19 Visual Odometry: 📃 Related Papers

Project 4 due

Week 11; Scene-Level Representations

Mar 26

Lec 20 Semantic Scene Graphs: 📃 Related Papers

Quiz 10

Mar 27

Dis 11Prelude to Data

Mar 28

Lec 21 Neural Radiance Fields: 📃 Related Papers

Quiz 11

Week 12; Data

Apr 2

Lec 22Datasets for Perception: 📃 Related Papers

Quiz 12

Apr 3

Dis 12Prelude to Perception for Manipulation

Apr 4

Lec 23Self-Supervised Learning: 📃 Related Papers

Quiz 13

Week 13; Perception for Manipulation

Apr 9

Lec 24Grasp Pose Detection: 📃 Related Papers

Quiz 14

Apr 10

Dis 13 Prelude to Transformer Architectures

Apr 11

Lec 25Tactile Perception for Grasping and Manipulation: 📃 Related Papers

Week 14; More Frontiers

Apr 16

Lec 26 Transformer Architectures: 📃 Related Papers

Quiz 15

Apr 17

Dis 14Remaining Challenges and Limitations

Apr 18

Lec 27More Frontiers: 📃 Related Papers

Week 15

Apr 23

Lec 28Project Demos:Course Closure: 📖 R. P. Feynman, Cargo Cult Science

Final Project Due