Carnegie Mellon University: Computer Vision Courses | Basic to Advanced
Carnegie Mellon University's Computer Vision courses offer a captivating journey into the world of visual perception, equipping students with the skills to unlock the secrets hidden within images.
Carnegie Mellon University's Computer Vision courses offer a captivating journey into the world of visual perception, equipping students with the skills to unlock the secrets hidden within images.
🌟💻 From foundational principles to cutting-edge techniques, these courses empower aspiring computer vision enthusiasts to explore the realm where pixels meet intelligence.
Computer Vision
Course Code: 16-385 | Session: Spring 2022
Short Description: This course offered by Carnegie Mellon University focuses on the fundamental concepts and techniques of computer vision. Students will learn about image formation, feature detection and matching, camera calibration, stereo vision, motion estimation, object recognition, and more. The course provides a comprehensive understanding of computer vision algorithms and their applications.
http://16385.courses.cs.cmu.edu/spring2022/
Learning for 3D Vision
Course Code: 16-889 | Session: Spring 2023
Short Description: This course at Carnegie Mellon University explores the field of learning for 3D vision. Students will delve into topics such as 3D reconstruction, shape analysis, depth estimation, and scene understanding using machine learning techniques. The course emphasizes both theoretical foundations and practical implementations in the context of 3D vision problems.
Computational Photography
Course Code: 15-463, 15-663, 15-862 | Session: Fall 2022
Short Description: Carnegie Mellon University offers this course on computational photography, which combines computer graphics, computer vision, and photography. Students will learn about image processing techniques, high dynamic range imaging, image-based lighting, image matting, and other advanced topics. The course explores how computational methods can enhance and manipulate digital photographs.
http://graphics.cs.cmu.edu/courses/15-463/
Physics-based Rendering
Course Code: 15-468, 15-668, 15-868 | Session: Spring 2023
Short Description: This course at Carnegie Mellon University focuses on physics-based rendering techniques used in computer graphics. Students will study light transport, global illumination, Monte Carlo methods, and material modeling. The course covers both theoretical foundations and practical implementations of rendering algorithms.
http://graphics.cs.cmu.edu/courses/15-468/
Learning-Based Image Synthesis
Code: 16-726 | Session: Spring 2023
Short Description: Carnegie Mellon University offers this course on learning-based image synthesis. Students will explore generative models, deep learning architectures, and neural rendering techniques for synthesizing realistic images. The course covers topics such as image generation, style transfer, texture synthesis, and image-to-image translation.
https://learning-image-synthesis.github.io/sp23/
Geometry-based Methods in VisionCourse Code: 16-822 | Session: Fall 2022
Short Description: This course at Carnegie Mellon University focuses on geometry-based methods in computer vision. Students will learn about geometric transformations, camera calibration, 3D reconstruction, structure from motion, and visual odometry. The course emphasizes the mathematical foundations and practical applications of geometric techniques in vision problems.
https://geometric3d.github.io/
Multiview 3D Geometry in Computer VisionCourse Code: CSCI 5980 | Session: Spring 2018
Short Description: Offered by Carnegie Mellon University, this course explores multiview 3D geometry in computer vision. Students will study topics such as camera models, epipolar geometry, stereo vision, multiple view geometry, and 3D reconstruction. The course provides a comprehensive understanding of the geometric principles underlying computer vision algorithms.
https://www-users.cse.umn.edu/~hspark/CSci5980/csci5980_3dvision.html
Visual Learning and Recognition
Course Code: 16-824 | Session: Spring 2023
Short Description: Carnegie Mellon University offers this course on visual learning and recognition. Students will study deep learning methods for image classification, object detection, semantic segmentation, and visual understanding. The course covers both foundational concepts and state-of-the-art techniques in visual recognition tasks.