This is the official repository for the assignments in the CS188 Computer Vision course at UCLA for the Winter 2023 term.
This course is designed to give you a broad introduction to computer vision with hands-on experience covering the basic concepts and techniques of deep learning. We will walk you through the course with four coding assignments. These assignments are designed for preparing you for advanced computer vision topics in the future, and you shall finish them independently.
The course aims to provide a broad introduction to computer vision and hands-on experience with deep learning concepts and techniques through four coding assignments, which are designed to prepare students for advanced computer vision topics in the future. Most of the assignments will be completed using Google Colab, a free Jupyter notebook environment that runs in the cloud and does not require any setup.
If you have any questions or concerns about the code or documents in this repository, please feel free to ask in Piazza and we will respond as soon as possible. We welcome any suggestions or contributions to improve this course.
We appreciate you for suggestion and contribution to improve this course!
To use this repository, students should follow these steps:
- Check the latest release when the instructor announces a new assignment is coming. Read the assignment document, which is the README.md file in the directory for each assignment.
- Clone or fork the repository to get the code or Jupyter notebooks on your computer.
- Fill in the empty functions, slots, or cells provided in the code.
- Follow the instructions in the code comments to ensure everything is working properly.
- Follow the submission instructions in the assignments to submit your work.
Here is a tentative schedule for the release and due dates of the assignments in this course:
- Assignment 1: Released on Sunday, Jan 15, due on Sunday, Jan 29
- Assignment 2: Released on Sunday, Jan 29, due on Sunday, Feb 12
- Assignment 3: Released on Sunday, Feb 12, due on Sunday, Feb 26
- Assignment 4: Released on Sunday, Feb 26, due on Sunday, Mar 12