For self study, the video recordings and lecture notes are provided in the Uva Deep Learning 1 Course.
Deep Learning 1, Deep Learning 2, Computer Vision 1, Computer Vision 2 (mainly 3D computer vision or a.k.a multiview geometry) are in the DataNose, under program list \ Master Artificial Intelligent.
- Stanford CS231n: Deep Learning for Computer Vision: Videos winter 2016 and lecture notes. Deep learning based 2D computer vision. There is also MIT 6.S191: Introduction to Deep Learning and Stanford CS 25 transformers united.
- Photogrammetry I & II by Cyrill Stachniss: Contains both tranditional and deep-learning based computer vision in 2D and 3D.
- Computer Vision by Andreas Geiger: Contains both tranditional and deep-learning based 2D and 3D computer vision.
- EfficientML.ai Lecture, Fall 2023, MIT 6.5940
- Photogrammetric Computer Vision by Cyrill Stachniss
- Multi View Geometry by Daniel Cremers: For in depth understdaning of multi view geometry, SfM (Structure from Motion), SLAM (Simultaneous Localization and Mapping). It is not a easy course.