CCS514

Computer Vision

Final Year Undergraduate Course • Spring 2026

Dr. Felix, Associate Professor of Computer Science

Computer vision is everywhere: search, self‑driving cars, medical imaging, drones, and augmented reality. This course dives deep into modern deep learning architectures for visual recognition tasks such as image classification, object detection, and segmentation. You will learn to implement and train neural networks from scratch, understand state‑of‑the‑art research, and apply multi‑million parameter models to real‑world problems. Prerequisites: Linear algebra, basic probability, and Python programming.

Lectures & Lab: Tue/Thu 2:00–4:00 Location: The Main Computer Lab

📅 Schedule 📝 Assignments 📚 Resources 👥 Staff

Weekly Schedule

Week	Topic	Readings (Modern Deep Learning Focus)
1	Introduction & Logistics (Slides)	Foundations of Computer Vision: 1, 2, 3
2	Image Classification (Classical & CNN basics) - (Slides)	CS231n: Linear classification VGGNet paper (Very Deep CNNs) ResNet paper (Deep Residual Learning)
3	Image Classification (Vision Transformer) - (Slides)	Vision Transformer (ViT) PyTorch CIFAR-10 tutorial
4	Object Detection (Two‑stage) - Slides	R‑CNN paper Fast R‑CNN Faster R‑CNN
5	Object Tracking - Slides	SORT (Simple Online Realtime Tracking) DeepSORT Trackformer (end‑to‑end tracking)
6	Object Detection (One‑stage)	YOLOv1 paper YOLOv2 / YOLO9000 SSD: Single Shot MultiBox Detector
7	Segmentation & Instance Segmentation	FCN (Fully Convolutional Networks) Mask R‑CNN DeepLab v3+ (semantic segmentation)
8	Pose Estimation	OpenPose (bottom‑up) HRNet (high‑resolution networks) ViTPose (vision transformer based)
9	Generative Models (GANs, Diffusion, VLMs)	GAN paper (Goodfellow) Denoising Diffusion Probabilistic Models (DDPM) CLIP (Vision‑Language Model) Stable Diffusion (latent diffusion) Diffusion models (review)
10	Exams Prep	-
11	Exams	-

Assignments

Assignment 1: Introduction
Due June 9th, 2026 – Click here to complete

Laboratory 1: Video Manipulation
Due June 11th, 2026 – ~~Click here to complete~~ - ~~Click here to submit~~ - Solution: Click to view

Laboratory 2: Image Classification
Due June 16th, 2026 - (~~Click here to complete~~)

Laboratory 3: Vision Transformer in Action
Click here to view

Laboratory 4: Object Detection with Ultralytics
Due: June 23rd, 2026 - (Click here to view)

Laboratory 5: Object Tracking with Ultralytics
Due: June 25th, 2026 - (Click here to view) (Click here to submit)

Grading Policy

10%

Attendance

20%

Assignments

70%

Final Exam

📌 All assignments must be submitted on time. Late submissions incur a 10% penalty per day. The final project includes a written report, code, and a short presentation.