News
Assignment 1 ReleaseWritten on 16.04.25 by Mohammad Amin Parchami Araghi Hi everyone, The first assignment is now released and can be accessed under the Materials tab on CMS. The deadline for this assignment is May 4th 23:59 CEST. As mentioned in the first tutorial, the assignment has two separate notebooks. The notebooks consist of code snippets and short text… Read more Hi everyone, The first assignment is now released and can be accessed under the Materials tab on CMS. The deadline for this assignment is May 4th 23:59 CEST. As mentioned in the first tutorial, the assignment has two separate notebooks. The notebooks consist of code snippets and short text blocks to be filled out. We are more than happy to help you with this assignment on the Forum. Kindly keep in mind that your posts are visible to all students and avoid posting your solutions. Please also remember that the deadline for forming teams on CMS is May 1st. Each team requires one submission by one of the members on CMS.
Lastly, there will be no tutorial on April 21st, due to public holiday!
All the best, Your HLCV Team
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First Tutorial, Monday 14.04Written on 10.04.25 by Mohammad Amin Parchami Araghi Hi everyone,
Welcome to the High-Level Computer Vision! We are very excited to have you in the course :) This is a friendly reminder that our first tutorial takes place on Monday April 14th in E1.5 002. We will start at 10:15 AM. The agenda for this tutorial is as follows: 1.… Read more Hi everyone,
Welcome to the High-Level Computer Vision! We are very excited to have you in the course :) This is a friendly reminder that our first tutorial takes place on Monday April 14th in E1.5 002. We will start at 10:15 AM. The agenda for this tutorial is as follows: 1. Discussing the tutorial and assignment structure. 2. Discussing the first assignment, to be released on the same week. 3. A Python tutorial.
All the best, Your HLCV Team
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High-Level Computer Vision
Overview
This course will cover essential techniques for high-level computer vision. These techniques facilitate semantic interpretation of visual data, as it is required for a broad range of applications like robotics, driver assistance, multi-media retrieval, surveillance, etc. In this area, the recognition and detection of objects, activities, and visual categories have seen dramatic progress over the last decade. We will discuss the methods that have led to a state-of-the-art performance in this area and provide the opportunity to gather hands-on experience with these techniques.
Course Information
Semester: Summer Semester
Year: 2025
Lecture: Wednesdays 10:00 AM - 12:00 PM (start at 10:15 AM)
Tutorial: Mondays 10:00 AM - 12:00 PM (start at 10:15 AM)
Location: E1.5 002
First Lecture: Wednesday April 9, 2025
First Tutorial: Monday April 14, 2025
Registration
Please register for the course in the CMS. If there are any issues, please write to hlcv-ss25@mpi-inf.mpg.de.
Lecturer: Prof. Dr. Bernt Schiele
TAs: Amin Parchami, Nhi Pham, Sophia Wiedmann, Mostafa Abdelgawad
Office Hour: Tuesday 10:00 AM - 11:00 AM, E1.4 629
Contacting TAs: hlcv-ss25@mpi-inf.mpg.de (please only use this email ID for all email communication with the TAs) or the Forum.
Literature:
- "Computer Vision: Algorithms and Applications" by Richard Szeliski (in particular chapter on image formation)
- "Probabilistic Topic Models" by Mark Steyvers, Tom Griffiths
- Mikolajcyk, Schmid: A Performance Evaluation of Local Descriptors, TPAMI, 2005
- Boiman, Shechtman, Irani: A Performance Evaluation of Local Descriptors, CVPR, 2008
- Gehler, Nowozin: On feature combination for multi class object classification, ICCV, 2009
- Krizhevsky, Sutskever, Hinton: ImageNet Classification with Deep Convolutional Networks, NIPS, 2012
- "Pattern recognition and machine learning" by Christopher M. Bishop
- "Computer vision" by David A. Forsyth and Jean Ponce