Computer Vision: From Fundamentals to Research Frontiers
“An 8-week intensive roadmap for a Physics SME to transition into a Machine Learning Researcher specializing in Computer Vision. This plan covers classical techniques, modern deep learning architectures, and cutting-edge research topics, emphasizing mathematical intuition and practical implementation.”
Week 1: Foundations of Image Processing & Classical Vision
By the end of this module you will be able to implement fundamental image manipulation and feature extraction algorithms from first principles.
Topics
Week 2: Deep Learning Foundations & Convolutional Neural Networks
By the end of this module you will be able to build, train, and debug a Convolutional Neural Network (CNN) from scratch for an image classification task.
Week 3: Modern CNN Architectures & Transfer Learning
By the end of this module you will be able to leverage state-of-the-art pre-trained models to solve custom image classification problems efficiently.
Week 4: Object Detection and Semantic Segmentation
By the end of this module you will be able to implement and train models for localizing and classifying multiple objects within an image.
Week 5: Generative Models in Vision
By the end of this module you will be able to understand the theory behind and implement deep generative models to synthesize novel images.
Week 6: Transformers in Vision
By the end of this module you will be able to adapt and apply Transformer-based architectures to computer vision tasks.
Week 7: 3D Vision and Multi-Modal Learning
By the end of this module you will be able to understand and experiment with models that reason about 3D scenes and connect vision with other modalities like text.
Week 8: Research Frontiers & Project Proposal
By the end of this module you will be able to identify a research gap in computer vision and formulate a structured proposal to address it.
References
Week 1: Week 1: Foundations of Image Processing & Classical Vision
Week 2: Week 2: Deep Learning Foundations & Convolutional Neural Networks
Week 3: Week 3: Modern CNN Architectures & Transfer Learning
Week 4: Week 4: Object Detection and Semantic Segmentation
Week 5: Week 5: Generative Models in Vision
Week 6: Week 6: Transformers in Vision
Vision_Transformer.ipynb - Colab
colab.research.google.comComputer Vision And Image Processing Fundamentals And ...Building a Vision Transformer from Scratch in PyTorchVision Transformers (ViT) Tutorial: Architecture and Code ...Tutorial 11: Vision Transformers — PyTorch Lightning 2.6.1 ...Tutorial 15: Vision Transformers — UvA DL Notebooks v1.2 ...Vision Transformers (ViTs): Computer Vision with Transformer ...
youtube.comBuilding a Vision Transformer from Scratch in PyTorch
geeksforgeeks.orgWeek 7: Week 7: 3D Vision and Multi-Modal Learning
Computer Vision And Image Processing Fundamentals And ...Learning for 3D VisionGitHub - mint-lab/3dv_tutorial: An Invitation to 3D Vision: A ...Lesson 7: 3D Computer Vision - btu.edu.geCVPR 2025 Tutorials3D Computer Vision - LearnOpenCVGetting Started with 3D Computer Vision in 2025 - OpenCV
youtube.comLearning for 3D Vision
learning3d.github.ioGitHub - mint-lab/3dv_tutorial: An Invitation to 3D Vision: A ...Lesson 7: 3D Computer Vision - btu.edu.geCVPR 2025 Tutorials3D Computer Vision - LearnOpenCVGetting Started with 3D Computer Vision in 2025 - OpenCV
github.comWeek 8: Week 8: Research Frontiers & Project Proposal
Computer Vision And Image Processing - Fundamentals And ...Computer-Vision-Tutorial/20_Research_Frontiers ... - GitHubCS 6384 Computer Vision Project Proposal DescriptionLectures | Introduction to Computer Visioncolab_tutorial.ipynb - ColabComputer Vision Tutorial - GeeksforGeeksCS231A – Computer vision Project proposals
youtube.comComputer-Vision-Tutorial/20_Research_Frontiers ... - GitHub
github.comCS 6384 Computer Vision Project Proposal Description
yuxng.github.ioCommunity Insights
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