Date	Topic	Reading	Items due
week 1 (Mon: 08/24)	Introduction to Computer Vision   Lecture Slides 1	Course logistics   Introduction to computer vision
week 1 (Wed: 08/26)	Image Filtering: cross-correlation   Lecture Slides 2   In-class activity #1 (image filtering cross-correlation)	Pillow concepts   Pillow tutorial   Image.open(path)   Image.save(path)   Image.new('L', (width, height), color=0)   Image.getpixel( (x,y) )   Image.putpixel( (x,y), value)   ImageDraw( img )
week 2 (Mon: 08/31)	Image Filtering: convolution   Lecture Slides 3     Notebook#1 (released on 08/31)
week 2 (Wed: 09/02)	Image-based Recognition   Image Classification and Neural Networks (NN)   Types of NN: Multilayer Perceptron (MLP)   Lecture Slides 4   Day04 Notes: PyTorch MLP	PyTorch Basics (review this before attempting activity#2)   PyTorch: nn.Linear()   PyTorch: nn.Sigmoid()   PyTorch: nn.Tanh()   PyTorch: nn.ReLU()
week 3 (Mon: 09/07)	Labor Day (university holiday; classes do not meet)		Notebook#1 (due on 09/07)
week 3 (Wed: 09/09)	Image-based Recognition   Image Classification and Neural Networks (NN)   Types of NN: Convolution Neural Network (CNN)   Lecture Slides 5   Day06 Notes: PyTorch CNN     Notebook #2 (released on 09/09)	PyTorch: nn.Conv2d()   PyTorch: nn.MaxPool2d()   PyTorch: nn.AvgPool2d()
week 4 (Mon: 09/14)	PyTorch Implementation   In-class activity #3 (PyTorch CNN)
week 4 (Wed: 09/16)	Popular Image Classification Networks (AlexNet, VGG, ResNet)   Dissecting Popular Pre-trained CNN models   Lecture Slides 8   AlexNet dissection   VGG-16 dissection   ResNet dissection		Notebook#2 (due on 09/16)
Week 5 (Mon: 09/21)	Fine-tuning a Pre-trained CNN model   Lecture Slides 9   Fine-tuning CNNs   Notebook#3 (Fine-tuning popular CNNs)
week 5 (Wed: 09/23)	Vision Transformer (ViT)   Other ViT variants (Swin Transformer Tiny)   ConvNext, Inflated-ConvNext Tiny   Lecture Slides 10   Vision Transformer (ViT) Dissection	The Hardware Lottery - Sara Hooker   Transformer (designed to win the hardware lottery)   Vision Transformer (ViT): Transformers for image recognition at scale
week 6 (Mon: 09/28)	Object Detection: Classical and Deep Learing-Based   Lecture Slides 11a: Classical Detectors   Lecture Slides 11b: Deep learning-based Detectors (Faster R-CNN, Mask R-CNN)		Notebook#3 (due on 10/02)
week 6 (Wed: 09/30)	Inference with Popular Object Detectors (Faster R-CNN, Mask R-CNN)   Lecture Slides 12   Inference with Object Detector with Faster R-CNN   Quiz#1 (released on Blackboard 09/30)
week 7 (Mon: 10/05)	Lecture Slides 13   Fine-tuning Popular Object Detectors (Faster R-CNN, Mask R-CNN)   Fine-tuning Object Detector: Detectron/Faster R-CNN     Notebook#4 (Fine-tuning Detectors: Faster & Mask R-CNN)
week 7 (Wed: 10/07)	Image Segmentation   Classical Segmentation (Felzenswalb, SLIC, clustering)   Lecture Slides 13 part1   Lecture Slides 13 part2   Classical Image Segmentation Codes		Quiz#2 (due on 10/07)
week 8 (Mon: 10/12)	Fall Break (classes do not meet)
week 8 (Wed: 10/14)	Vision Foundation Model for Image Segmentation: Segment Anything (SAM)   Lecture Slides 14 [pptx]   Inference with SAM: Automatically generating object masks with Segment Anything (SAM)		Notebook#4 (due on 10/14)
week 9 (Mon: 10/19)	Semantic Segmentaiton   Popular Semantic Segmentation Models (U-Net, FCN, SegNet, PSPNet)   Lecture Slides 15     Notebook #5 (Semantic Segmentation Inference and Training with UNet)
week 9 (Wed: 10/21)	Probability Basics   Discrete Probability Distribution   Lecture Slides 16 part1   Discrte probability distribution code   Continous Probability Distribution   Gaussian Distributions   Lecture Slides 16 part2   In-class activity#5: Continous probability distribution
week 10 (Mon: 10/26)	Image Generation and Deep Generative Models: Generative Adversarial Network (GAN)   Lecture Slides 17	AI Art
week 10 (Wed: 10/28)	Maximum Likelihood (ML) Estimate   Lecture Slides 18 part1   In-class activity#6: Maximum likelihood estimate for Gaussian distribution   Image Generation and Deep Generative Models: Variational Auto Encoder (VAE)   Lecture Slides 18 part2   Quiz#2 (released on 10/28)	Tutorial on variational autoencoder by Carl Doersch   Generating Counterfactual Images: C2C-VAE - CBREIS'22   Generative model: implicit reparameterization   Wasserstein Distance
Week 11 (Mon: 11/02)	Image Generation and Deep Generative Models: Variational Auto Encoder (VAE)   Lecture Slides 18 part2 (continued)   In-class activity#7: VAE code for digit image generation using MNIST dataset		Notebook#5 (due on 11/02)
Week 11 (Wed: 11/04)	Image Generation and Deep Generative Models: Diffusion Model   Lecture Slidees 19   In-class activity#8: Generating images from text prompt using Stable Diffusion Model	Diffusion models are evolutionary algorithms - arxiv'24	Quiz#2 (due on 11/04)
Week 12 (Mon: 11/09)	Image Transformation   Linear transformation   Lecture Slidees 20   In-class activity#8: Rotation, Scaling, Shearing transformation
Week 12 (Wed: 11/11)
Week 13 (Mon: 11/16)	Homogenous coordinates   Affine and projective transformation   Lecture Slides 21 part1     Camera Projection   Modeling projection   Activity: projection practice   Generalizing the model   Adding a lens   Lecture Slides 21 part2	From Images to 3D Models-ACM Communication'2002
Week 13 (Wed: 11/18)	Classical 3D Reconstruction (Part#1)   Monocular Depth Estimation: 3D Reconstruction from Single Images   Stereo Matching: 3D Reconstruction from Two Images   Multiview Stereo: 3D Reconstruction from Multiple Images   Lecture Slides		Final Project Presentation on 12/11
Week 14 (Mon: 11/23)	Deep Learning-based 3D Reconstruction (Part#2)   Monocular Depth Estimation Demo   Stereo Matching Demo   Multiview Stereo Demo   Lecture Slides
week 14 (Wed: 11/25)	Thanksgiving Break (classes do not meet)
Week 15 (Mon: 11/30)	Large Multimodal Model (LMM)   LMM Application using PyTorch   Lecture Slides 27	Reading:   Dissociating language and thought in large language models-2024   Is OpenAI-o1 reasoning? (ML Street Talk'24)   World Model (Jurgen Schmidhuber@NeurIPS'18)   LoRA: Low-Rank Adaptation of Large Language Models (ICLR'22)
Week 15 (Wed: 12/02)	Final project group presentation   Location: Collier-Scripps#335   Quiz#3 (released on 12/02)   Course Evaluation
Week 16 (Monday: 12/07)	No final exam!	Reading:	Q3 (due on 12/07)   Final Project Code +   Presentation Slides (due by 12/11)