# Course - Computer Vision MT25

> Source: https://ollybritton.com/notes/uni/part-c/mt25/computer-vision/ · Updated: 2026-05-18 · Tags: uni, course

- [Course webpage](https://courses.cs.ox.ac.uk/course/view.php?name=vision_2025_2026) ([old](https://courses.cs.ox.ac.uk/course/view.php?id=698))
- Lecture notes (from previous year)
	- [1, Introduction](https://courses.cs.ox.ac.uk/pluginfile.php/19895/mod_label/intro/01-Introduction.pdf)
	- [2, Image enhancement](https://courses.cs.ox.ac.uk/pluginfile.php/19895/mod_label/intro/02-Filtering.pdf?time=1738714783416)
	- [3, 2D Fourier transforms and applications](https://courses.cs.ox.ac.uk/pluginfile.php/19895/mod_label/intro/03-FourierTransforms.pdf?time=1738714805639)
	- [4, Image restoration](https://courses.cs.ox.ac.uk/pluginfile.php/19895/mod_label/intro/04-Restoration.pdf?time=1738714828444)
	- [5, Matching, indexing, and search](https://courses.cs.ox.ac.uk/pluginfile.php/19895/mod_label/intro/05-MatchingIndexingSearch.pdf?time=1738714859204)
	- [6, Image classification](https://courses.cs.ox.ac.uk/pluginfile.php/19895/mod_label/intro/06-Classification.pdf?time=1738714882358)
	- [7, Convolutional networks](https://courses.cs.ox.ac.uk/pluginfile.php/19895/mod_label/intro/07-CNNs.pdf)
	- [8, Transformer networks for images](https://courses.cs.ox.ac.uk/pluginfile.php/19895/mod_label/intro/08-Transformers.pdf)
	- [9, Visualisation and understanding](https://courses.cs.ox.ac.uk/pluginfile.php/19895/mod_label/intro/09-VisualizationUnderstanding.pdf)
	- [10, Object detection](https://courses.cs.ox.ac.uk/pluginfile.php/19895/mod_label/intro/10-ObjectDetection.pdf)
	- [11, Image segmentation](https://courses.cs.ox.ac.uk/pluginfile.php/19895/mod_label/intro/11-Segmentation.pdf)
	- [12, Videos](https://courses.cs.ox.ac.uk/pluginfile.php/19895/mod_label/intro/12-Videos.pdf)
	- [13, Tracking](https://courses.cs.ox.ac.uk/pluginfile.php/19895/mod_label/intro/13-Tracking.pdf)
	- [14, Camera models and triangulation](https://courses.cs.ox.ac.uk/pluginfile.php/19895/mod_label/intro/14-CameraModels.pdf)
	- [15, Multiple view geometry](https://courses.cs.ox.ac.uk/pluginfile.php/19895/mod_label/intro/15-MVG.pdf)
	- [16, Generative models](https://courses.cs.ox.ac.uk/pluginfile.php/19895/mod_label/intro/16-GenerativeModels.pdf)
	- [17, Representation learning](https://courses.cs.ox.ac.uk/pluginfile.php/19895/mod_label/intro/17-RepresentationLearning.pdf)
	- [18, Unsupervised computer vision](https://courses.cs.ox.ac.uk/pluginfile.php/19895/mod_label/intro/18-Unsupervised.pdf)
	- [19, Vision and language](https://courses.cs.ox.ac.uk/pluginfile.php/19895/mod_label/intro/19-VisionLanguage.pdf)
	- [20, Ethics and privacy](https://courses.cs.ox.ac.uk/pluginfile.php/19895/mod_label/intro/20-EthicsPrivacy.pdf)
- My notes here are based primarily on the slides  above, written by [Prof. Christian Rupprecht](https://chrirupp.github.io/).
- Lecture recordings
	- [2024-2025](https://ox.cloud.panopto.eu/Panopto/Pages/Sessions/List.aspx#folderID=%22fd3b9130-f466-466a-9147-b1ea00e85edc%22)
	- [2025-2026](https://ox.cloud.panopto.eu/Panopto/Pages/Sessions/List.aspx#folderID=%2219228d19-5e0b-4fd5-8315-b36300953973%22)
- [Practicals](https://github.com/chrirupp/cv_course)
- Other courses this term: [Courses MT25](https://ollybritton.com/notes/uni/part-a/mt25/)

### Notes
- [Notes - Computer Vision MT25, Overview of results and methods](https://ollybritton.com/notes/uni/part-c/mt25/computer-vision/notes/overview-of-results-and-methods/)

- [Notes - Computer Vision MT25, Image representation](https://ollybritton.com/notes/uni/part-c/mt25/computer-vision/notes/image-representation/)
- [Notes - Computer Vision MT25, Sampling and reconstruction](https://ollybritton.com/notes/uni/part-c/mt25/computer-vision/notes/sampling-and-reconstruction/)
- [Notes - Computer Vision MT25, Subsampling and upsampling](https://ollybritton.com/notes/uni/part-c/mt25/computer-vision/notes/subsampling-and-upsampling/)
- [Notes - Computer Vision MT25, Image transformations](https://ollybritton.com/notes/uni/part-c/mt25/computer-vision/notes/image-transformations/)
- [Notes - Computer Vision MT25, Homogenous coordinates and homographies](https://ollybritton.com/notes/uni/part-c/mt25/computer-vision/notes/homogenous-coordinates-and-homographies/)
- [Notes - Computer Vision MT25, Convolutions](https://ollybritton.com/notes/uni/part-c/mt25/computer-vision/notes/convolutions/)
- [Notes - Computer Vision MT25, Filtering](https://ollybritton.com/notes/uni/part-c/mt25/computer-vision/notes/filtering/)
- [Notes - Computer Vision MT25, Fourier transform](https://ollybritton.com/notes/uni/part-c/mt25/computer-vision/notes/fourier-transform/)
- [Notes - Computer Vision MT25, Image restoration](https://ollybritton.com/notes/uni/part-c/mt25/computer-vision/notes/image-restoration/)
- [Notes - Computer Vision MT25, Correspondences](https://ollybritton.com/notes/uni/part-c/mt25/computer-vision/notes/correspondences/)
- [Notes - Computer Vision MT25, Scale-invariant feature transform](https://ollybritton.com/notes/uni/part-c/mt25/computer-vision/notes/scale-invariant-feature-transform/)
- [Notes - Computer Vision MT25, Image classification](https://ollybritton.com/notes/uni/part-c/mt25/computer-vision/notes/image-classification/)
- [Notes - Computer Vision MT25, Neural networks](https://ollybritton.com/notes/uni/part-c/mt25/computer-vision/notes/neural-networks/)
- [Notes - Computer Vision MT25, Loss function design](https://ollybritton.com/notes/uni/part-c/mt25/computer-vision/notes/loss-function-design/)
- [Notes - Computer Vision MT25, Convolutional neural networks](https://ollybritton.com/notes/uni/part-c/mt25/computer-vision/notes/convolutional-neural-networks/)
- [Notes - Computer Vision MT25, Dropout](https://ollybritton.com/notes/uni/part-c/mt25/computer-vision/notes/dropout/)
- [Notes - Computer Vision MT25, Learning curves](https://ollybritton.com/notes/uni/part-c/mt25/computer-vision/notes/learning-curves/)
- [Notes - Computer Vision MT25, Attention and transformers](https://ollybritton.com/notes/uni/part-c/mt25/computer-vision/notes/attention-and-transformers/)
- [Notes - Computer Vision MT25, Interpreting vision models](https://ollybritton.com/notes/uni/part-c/mt25/computer-vision/notes/interpreting-vision-models/)
- [Notes - Computer Vision MT25, Object detection](https://ollybritton.com/notes/uni/part-c/mt25/computer-vision/notes/object-detection/)
- [Notes - Computer Vision MT25, Precision and recall](https://ollybritton.com/notes/uni/part-c/mt25/computer-vision/notes/precision-and-recall/)
- [Notes - Computer Vision MT25, Segmentation](https://ollybritton.com/notes/uni/part-c/mt25/computer-vision/notes/segmentation/)
- [Notes - Computer Vision MT25, Video](https://ollybritton.com/notes/uni/part-c/mt25/computer-vision/notes/video/)
- [Notes - Computer Vision MT25, Optical flow](https://ollybritton.com/notes/uni/part-c/mt25/computer-vision/notes/optical-flow/)
- [Notes - Computer Vision MT25, Visual tracking](https://ollybritton.com/notes/uni/part-c/mt25/computer-vision/notes/visual-tracking/)
- [Notes - Computer Vision MT25, Lucas-Kanade tracking](https://ollybritton.com/notes/uni/part-c/mt25/computer-vision/notes/lucas-kanade-tracking/)
- [Notes - Computer Vision MT25, Camera models](https://ollybritton.com/notes/uni/part-c/mt25/computer-vision/notes/camera-models/)
- [Notes - Computer Vision MT25, Multiple view geometry](https://ollybritton.com/notes/uni/part-c/mt25/computer-vision/notes/multiple-view-geometry/)
- [Notes - Computer Vision MT25, Neural rendering](https://ollybritton.com/notes/uni/part-c/mt25/computer-vision/notes/neural-rendering/)
- [Notes - Computer Vision MT25, Generative models](https://ollybritton.com/notes/uni/part-c/mt25/computer-vision/notes/generative-models/)
- [Notes - Computer Vision MT25, Representation learning](https://ollybritton.com/notes/uni/part-c/mt25/computer-vision/notes/representation-learning/)
- [Notes - Computer Vision MT25, Unsupervised computer vision](https://ollybritton.com/notes/uni/part-c/mt25/computer-vision/notes/unsupervised-computer-vision/)
- [Notes - Computer Vision MT25, Vision and language](https://ollybritton.com/notes/uni/part-c/mt25/computer-vision/notes/vision-and-language/)
- [Notes - Computer Vision MT25, Ethics and privacy](https://ollybritton.com/notes/uni/part-c/mt25/computer-vision/notes/ethics-and-privacy/)

### Related notes
The majority of [Course - Machine Learning MT23](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/) is relevant, but especially:

- [Notes - Machine Learning MT23, Classification](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/classification/)
- [Notes - Machine Learning MT23, Clustering](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/clustering/)
- [Notes - Machine Learning MT23, Convolutional neural networks](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/convolutional-neural-networks/)
- [Notes - Machine Learning MT23, Cross-entropy loss](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/cross-entropy-loss/)
- [Notes - Machine Learning MT23, Generative models](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/generative-models/)
- [Notes - Machine Learning MT23, Linear regression](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/linear-regression/)
- [Notes - Machine Learning MT23, Logistic regression](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/logistic-regression/)
- [Notes - Machine Learning MT23, Matrix calculus](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/matrix-calculus/)
- [Notes - Machine Learning MT23, Maximum likelihood principle](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/maximum-likelihood-principle/)
- [Notes - Machine Learning MT23, Naïve Bayes classifiers](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/naive-bayes-classifiers/)
- [Notes - Machine Learning MT23, Neural networks](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/neural-networks/)
- [Notes - Machine Learning MT23, Perceptrons](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/perceptrons/)
- [Notes - Machine Learning MT23, Principal component analysis](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/principal-component-analysis/)
- [Notes - Machine Learning MT23, Support vector machines](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/support-vector-machines/)
- [Notes - Machine Learning MT23, k-means clustering](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/k-means-clustering/)
- [Notes - Machine Learning MT23, k-nearest neighbours](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/k-nearest-neighbours/)
- [Paper - Attention Is All You Need (2017)](https://ollybritton.com/notes/uni/part-c/mt25/theories-of-deep-learning/reading/paper-attention-is-all-you-need-2017/)

Surprisingly, there is a small amount of overlap with the content covered in

- [Notes - Complex Analysis MT23, Extended complex plane](https://ollybritton.com/notes/uni/part-a/mt23/complex-analysis/notes/extended-complex-plane/)
- [Notes - Complex Analysis MT23, Möbius maps](https://ollybritton.com/notes/uni/part-a/mt23/complex-analysis/notes/mobius-maps/)

when it comes to homogenous coordinates and the projective line model of the complex plane.

### Problem Sheets
- [Sheet 1 (old)](https://courses.cs.ox.ac.uk/pluginfile.php/20293/mod_resource/content/1/cv_course_sheet1.pdf), [redacted](https://ollybritton.com/404)
- [Sheet 2 (old)](https://courses.cs.ox.ac.uk/pluginfile.php/20634/mod_resource/content/1/cv_course_sheet2.pdf), [redacted](https://ollybritton.com/404)
- [Sheet 3 (old)](https://courses.cs.ox.ac.uk/pluginfile.php/20829/mod_resource/content/2/cv_course_sheet3.pdf), [redacted](https://ollybritton.com/404)
- [Sheet 4 (old)](https://courses.cs.ox.ac.uk/pluginfile.php/21539/mod_resource/content/2/cv_course_sheet4.pdf), [redacted](https://ollybritton.com/404)

### To-Do List

#### Priority gaps

##### Priority 1 (exam-tested or central bookwork)

##### Priority 2 (clean bookwork from slides)

##### Priority 3 (slide content, lower exam frequency)

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