Yes, there are several excellent video lectures available on computer vision, ranging from introductory to advanced levels. These lectures cover key topics such as image processing, convolutional neural networks (CNNs), object detection, and semantic segmentation. Depending on your familiarity with the subject, you can choose courses or lectures that suit your skill level and learning objectives.
For beginners, Stanford's "CS231n: Convolutional Neural Networks for Visual Recognition" by Fei-Fei Li, Justin Johnson, and Serena Yeung is a great starting point. The lectures provide a solid foundation in the mathematical and algorithmic principles behind computer vision and include practical coding exercises. The course is available for free on YouTube and includes lectures on CNNs, backpropagation, and modern architectures like ResNet and GANs.
If you're looking for more applied knowledge, consider the "Deep Learning for Computer Vision" specialization on Coursera by Andrew Ng’s team at DeepLearning.AI. It focuses on practical applications like facial recognition and object detection while balancing theoretical insights. Another option is MIT's "6.S191: Introduction to Deep Learning," which covers computer vision as part of broader AI topics, often including cutting-edge advancements and project demos.