Advanced Deep Learning for Computer vision (ADL4CV) (IN2389)

Welcome to the Advanced Deep Learning for Computer Vision course offered in WS21.

Lecture

Date and location: Until further notice, all lectures will be held online.

Lecturers: Prof. Dr. Laura Leal-Taixé and Ismail Elezi

ECTS: 8

2V + 3P

Due to COVID-19, all lectures will be recorded!

Practical

Tutors: Aysim Toker, Tim Meinhardt, Jenny Seidenschwarz, and Sergio Agostinho

The practical part of the course will consist of a semester-long project in teams of 2. There will be weekly presentations of the projects throughout the semester.

Lecture

• Lecture 0: Course information
• Lecture 1: Visualization
• Lecture 2: Siamese networks and similarity learning
• Lecture 3: Autoencoders and VAE
• Lecture 4: Deep Learning on Graphs
• Lecture 5: GANs 1
• Lecture 6: GANs 2
• Lecture 7: Autoregressive models
• Lecture 8: Transformers
• Lecture 9: Semi-supervised learning
• Lecture 10: Active learning

Exam

February 23rd, 11:30-12:30

The exam will be written and online.

Slides

You can download the slides in PDF format on Moodle.

Videos

You will find all videos for this semester on YouTube.

You can find all videos for this semester here:

• YouTube Playlist

Prerequisites

• Introduction to Deep Learning (I2DL) (IN2346)
• Strong mathematical background: Linear algebra and calculus.
• Previous knowledge of Python is mandatory.
• Previous knowledge of PyTorch is highly recommended.

Moodle

We use Moodle for discussions and to distribute important information. Please check the News and Discussion boards regularly or subscribe to them. The slides and all material will also be posted on Moodle.

Contact us

If you have any questions regarding the organization of the course, do not hesitate to contact us at: adl4cv@dvl.in.tum.de

For questions on the syllabus, exercises or any other questions on the content of the lecture, we will use the Moodle discussion board.