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    <title>Computer Vision Group teaching:ss2024</title>
    <subtitle></subtitle>
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    <id>https://cvg.cit.tum.de/</id>
    <updated>2026-04-22T01:43:26+00:00</updated>
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    <entry>
        <title>Master Seminar: 3D Shape Matching and Application in Computer Vision (5 ECTS)</title>
        <link rel="alternate" type="text/html" href="https://cvg.cit.tum.de/teaching/ss2024/3dsm?rev=1729591469&amp;do=diff"/>
        <published>2024-10-22T10:04:29+00:00</published>
        <updated>2024-10-22T10:04:29+00:00</updated>
        <id>https://cvg.cit.tum.de/teaching/ss2024/3dsm?rev=1729591469&amp;do=diff</id>
        <author>
            <name>Anonymous</name>
            <email>anonymous@undisclosed.example.com</email>
        </author>
        <category  term="teaching:ss2024" />
        <content>----------

Master Seminar: 3D Shape Matching and Application in Computer Vision (5 ECTS)

 Summer Semester 2024, TU München 

Organisers: 
Viktoria Ehm, Maolin Gao

2024-04-30: We&#039;ve updated the presentation schedule on 16.05 and 23.05.2024.

2024-04-18: Our weekly seminar will take place on</content>
        <summary>----------

Master Seminar: 3D Shape Matching and Application in Computer Vision (5 ECTS)

 Summer Semester 2024, TU München 

Organisers: 
Viktoria Ehm, Maolin Gao

2024-04-30: We&#039;ve updated the presentation schedule on 16.05 and 23.05.2024.

2024-04-18: Our weekly seminar will take place on</summary>
    </entry>
    <entry>
        <title>Practical Course: Applied Foundation Models in Computer Vision (10 ECTS)</title>
        <link rel="alternate" type="text/html" href="https://cvg.cit.tum.de/teaching/ss2024/afm?rev=1707227252&amp;do=diff"/>
        <published>2024-02-06T13:47:32+00:00</published>
        <updated>2024-02-06T13:47:32+00:00</updated>
        <id>https://cvg.cit.tum.de/teaching/ss2024/afm?rev=1707227252&amp;do=diff</id>
        <author>
            <name>Anonymous</name>
            <email>anonymous@undisclosed.example.com</email>
        </author>
        <category  term="teaching:ss2024" />
        <content>Practical Course: Applied Foundation Models in Computer Vision (10 ECTS)

News

The preliminary meeting will take place on Feb 7th, 2024 at 2pm under the following link:

&lt;https://tum-conf.zoom-x.de/j/63369197429?pwd=aVFseGlBRkd5Sloxc0YyUWlOSlp5dz09&gt;

The course itself will be conducted in person.

----------

Organizational

Organizers</content>
        <summary>Practical Course: Applied Foundation Models in Computer Vision (10 ECTS)

News

The preliminary meeting will take place on Feb 7th, 2024 at 2pm under the following link:

&lt;https://tum-conf.zoom-x.de/j/63369197429?pwd=aVFseGlBRkd5Sloxc0YyUWlOSlp5dz09&gt;

The course itself will be conducted in person.

----------

Organizational

Organizers</summary>
    </entry>
    <entry>
        <title>Practical Course: Creation of Deep Learning Methods (10 ECTS)</title>
        <link rel="alternate" type="text/html" href="https://cvg.cit.tum.de/teaching/ss2024/create_dl?rev=1719395084&amp;do=diff"/>
        <published>2024-06-26T09:44:44+00:00</published>
        <updated>2024-06-26T09:44:44+00:00</updated>
        <id>https://cvg.cit.tum.de/teaching/ss2024/create_dl?rev=1719395084&amp;do=diff</id>
        <author>
            <name>Anonymous</name>
            <email>anonymous@undisclosed.example.com</email>
        </author>
        <category  term="teaching:ss2024" />
        <content>----------

Practical Course: Creation of Deep Learning Methods (10 ECTS)

 Summer Semester 2024, TU Munich 

Please send applications (including learning goals, programming skills description, code, all grade transcripts (small PDF file size) - see preliminary-meeting slides) to create-dl[at]vision.in.tum.de</content>
        <summary>----------

Practical Course: Creation of Deep Learning Methods (10 ECTS)

 Summer Semester 2024, TU Munich 

Please send applications (including learning goals, programming skills description, code, all grade transcripts (small PDF file size) - see preliminary-meeting slides) to create-dl[at]vision.in.tum.de</summary>
    </entry>
    <entry>
        <title>Computer Vision II: Multiple View Geometry (IN2228)</title>
        <link rel="alternate" type="text/html" href="https://cvg.cit.tum.de/teaching/ss2024/cv2?rev=1745409526&amp;do=diff"/>
        <published>2025-04-23T11:58:46+00:00</published>
        <updated>2025-04-23T11:58:46+00:00</updated>
        <id>https://cvg.cit.tum.de/teaching/ss2024/cv2?rev=1745409526&amp;do=diff</id>
        <author>
            <name>Anonymous</name>
            <email>anonymous@undisclosed.example.com</email>
        </author>
        <category  term="teaching:ss2024" />
        <content>Computer Vision II: Multiple View Geometry (IN2228)

Overview

The lecture introduces the basic concepts of image formation - perspective projection and camera motion. The goal is to reconstruct the three-dimensional world and the camera motion from multiple images. To this end, one determines correspondences between points in various images and respective constraints that allow to compute motion and 3D structure. A particular emphasis of the lecture is on mathematical descriptions of rigid body…</content>
        <summary>Computer Vision II: Multiple View Geometry (IN2228)

Overview

The lecture introduces the basic concepts of image formation - perspective projection and camera motion. The goal is to reconstruct the three-dimensional world and the camera motion from multiple images. To this end, one determines correspondences between points in various images and respective constraints that allow to compute motion and 3D structure. A particular emphasis of the lecture is on mathematical descriptions of rigid body…</summary>
    </entry>
    <entry>
        <title>Seminar: Deep Learning for the Natural Sciences (5 ECTS)</title>
        <link rel="alternate" type="text/html" href="https://cvg.cit.tum.de/teaching/ss2024/dl4science?rev=1722954758&amp;do=diff"/>
        <published>2024-08-06T14:32:38+00:00</published>
        <updated>2024-08-06T14:32:38+00:00</updated>
        <id>https://cvg.cit.tum.de/teaching/ss2024/dl4science?rev=1722954758&amp;do=diff</id>
        <author>
            <name>Anonymous</name>
            <email>anonymous@undisclosed.example.com</email>
        </author>
        <category  term="teaching:ss2024" />
        <content>----------

Seminar: Deep Learning for the Natural Sciences (5 ECTS)

 Summer Semester 2024

Organiser: 
Karnik Ram, Annalena Kofler

Description

Following its success in computer vision and language processing, deep learning is now being increasingly used to augment and accelerate research in the natural sciences. Examples include electro-catalyst discovery for energy storage, fast PDE solvers for weather forecasting, discovery of new anti-biotics, and many other advances that were not possibl…</content>
        <summary>----------

Seminar: Deep Learning for the Natural Sciences (5 ECTS)

 Summer Semester 2024

Organiser: 
Karnik Ram, Annalena Kofler

Description

Following its success in computer vision and language processing, deep learning is now being increasingly used to augment and accelerate research in the natural sciences. Examples include electro-catalyst discovery for energy storage, fast PDE solvers for weather forecasting, discovery of new anti-biotics, and many other advances that were not possibl…</summary>
    </entry>
    <entry>
        <title>Practical Course: Expert-Level Deep Learning (10 ECTS)</title>
        <link rel="alternate" type="text/html" href="https://cvg.cit.tum.de/teaching/ss2024/dlpractice?rev=1719395094&amp;do=diff"/>
        <published>2024-06-26T09:44:54+00:00</published>
        <updated>2024-06-26T09:44:54+00:00</updated>
        <id>https://cvg.cit.tum.de/teaching/ss2024/dlpractice?rev=1719395094&amp;do=diff</id>
        <author>
            <name>Anonymous</name>
            <email>anonymous@undisclosed.example.com</email>
        </author>
        <category  term="teaching:ss2024" />
        <content>----------

Practical Course: Expert-Level Deep Learning (10 ECTS)

 Summer Semester 2024, TU Munich 

Please send applications (including learning goals, programming skills description, code, all grade transcripts (small PDF file size) - see preliminary-meeting slides) to dlpractice[at]vision.in.tum.de</content>
        <summary>----------

Practical Course: Expert-Level Deep Learning (10 ECTS)

 Summer Semester 2024, TU Munich 

Please send applications (including learning goals, programming skills description, code, all grade transcripts (small PDF file size) - see preliminary-meeting slides) to dlpractice[at]vision.in.tum.de</summary>
    </entry>
    <entry>
        <title>Seminar: Advanced topics in Graph Learning (5 ECTS)</title>
        <link rel="alternate" type="text/html" href="https://cvg.cit.tum.de/teaching/ss2024/graph_learning_ss24?rev=1716371744&amp;do=diff"/>
        <published>2024-05-22T09:55:44+00:00</published>
        <updated>2024-05-22T09:55:44+00:00</updated>
        <id>https://cvg.cit.tum.de/teaching/ss2024/graph_learning_ss24?rev=1716371744&amp;do=diff</id>
        <author>
            <name>Anonymous</name>
            <email>anonymous@undisclosed.example.com</email>
        </author>
        <category  term="teaching:ss2024" />
        <content>Seminar: Advanced topics in Graph Learning (5 ECTS)

Summer Semester 2024, TU München

Organizers: 
 Christian Koke,  Abhishek Saroha

Correspondence

Please forward any queries related to the seminar to: &lt;Abhishek.Saroha@in.tum.de&gt;.


Course Content

The field of graph learning has recently witnessed a significant surge in interest with with emerging applications of networks on graph structured data ranging from topics in drug discovery over traffic control to guiding mathematicians intuition i…</content>
        <summary>Seminar: Advanced topics in Graph Learning (5 ECTS)

Summer Semester 2024, TU München

Organizers: 
 Christian Koke,  Abhishek Saroha

Correspondence

Please forward any queries related to the seminar to: &lt;Abhishek.Saroha@in.tum.de&gt;.


Course Content

The field of graph learning has recently witnessed a significant surge in interest with with emerging applications of networks on graph structured data ranging from topics in drug discovery over traffic control to guiding mathematicians intuition i…</summary>
    </entry>
    <entry>
        <title>Seminar: Advanced topics in Graph Learning (5 ECTS)</title>
        <link rel="alternate" type="text/html" href="https://cvg.cit.tum.de/teaching/ss2024/graph_learning_ws24?rev=1725523793&amp;do=diff"/>
        <published>2024-09-05T08:09:53+00:00</published>
        <updated>2024-09-05T08:09:53+00:00</updated>
        <id>https://cvg.cit.tum.de/teaching/ss2024/graph_learning_ws24?rev=1725523793&amp;do=diff</id>
        <author>
            <name>Anonymous</name>
            <email>anonymous@undisclosed.example.com</email>
        </author>
        <category  term="teaching:ss2024" />
        <content>Seminar: Advanced topics in Graph Learning (5 ECTS)

Summer Semester 2024, TU München

Organizers: 
 Christian Koke,  Abhishek Saroha

Correspondence

Please forward any queries related to the seminar to: &lt;Abhishek.Saroha@in.tum.de&gt;.


Course Content

The field of graph learning has recently witnessed a significant surge in interest with with emerging applications of networks on graph structured data ranging from topics in drug discovery over traffic control to guiding mathematicians intuition i…</content>
        <summary>Seminar: Advanced topics in Graph Learning (5 ECTS)

Summer Semester 2024, TU München

Organizers: 
 Christian Koke,  Abhishek Saroha

Correspondence

Please forward any queries related to the seminar to: &lt;Abhishek.Saroha@in.tum.de&gt;.


Course Content

The field of graph learning has recently witnessed a significant surge in interest with with emerging applications of networks on graph structured data ranging from topics in drug discovery over traffic control to guiding mathematicians intuition i…</summary>
    </entry>
    <entry>
        <title>Practical Course: Geometric Scene Understanding (10 ECTS)</title>
        <link rel="alternate" type="text/html" href="https://cvg.cit.tum.de/teaching/ss2024/gsu?rev=1720686144&amp;do=diff"/>
        <published>2024-07-11T08:22:24+00:00</published>
        <updated>2024-07-11T08:22:24+00:00</updated>
        <id>https://cvg.cit.tum.de/teaching/ss2024/gsu?rev=1720686144&amp;do=diff</id>
        <author>
            <name>Anonymous</name>
            <email>anonymous@undisclosed.example.com</email>
        </author>
        <category  term="teaching:ss2024" />
        <content>----------

Practical Course: Geometric Scene Understanding (10 ECTS)

Overview

This practical course aims at advanced students with prior knowledge of deep learning (e.g. Introduction to Deep Learning, IN2346) and multi-view geometry (e.g. Computer Vision II, IN2228). The goal of this course is to gain practical experience with state-of-the-art computer vision models and implement innovative ideas tackling open real-world challenges.</content>
        <summary>----------

Practical Course: Geometric Scene Understanding (10 ECTS)

Overview

This practical course aims at advanced students with prior knowledge of deep learning (e.g. Introduction to Deep Learning, IN2346) and multi-view geometry (e.g. Computer Vision II, IN2228). The goal of this course is to gain practical experience with state-of-the-art computer vision models and implement innovative ideas tackling open real-world challenges.</summary>
    </entry>
    <entry>
        <title>Master Seminar - HuMANS: 3D Human Motion Analysis (5 ECTS)</title>
        <link rel="alternate" type="text/html" href="https://cvg.cit.tum.de/teaching/ss2024/humans?rev=1713202320&amp;do=diff"/>
        <published>2024-04-15T17:32:00+00:00</published>
        <updated>2024-04-15T17:32:00+00:00</updated>
        <id>https://cvg.cit.tum.de/teaching/ss2024/humans?rev=1713202320&amp;do=diff</id>
        <author>
            <name>Anonymous</name>
            <email>anonymous@undisclosed.example.com</email>
        </author>
        <category  term="teaching:ss2024" />
        <content>----------

Master Seminar - HuMANS: 3D Human Motion Analysis (5 ECTS)

 Summer Semester 2024, TU München 

Organisers: 
Cecilia Curreli, Mariia Gladkova

Please direct all questions to  humans-ss24@vision.in.tum.de

Description

In this seminar, we are taking a brief glimpse at some of the very recent works conducted in the area of human motion analysis and generation. We would discuss various research directions such as 4D reconstruction and novel view synthesis, human pose estimation and moti…</content>
        <summary>----------

Master Seminar - HuMANS: 3D Human Motion Analysis (5 ECTS)

 Summer Semester 2024, TU München 

Organisers: 
Cecilia Curreli, Mariia Gladkova

Please direct all questions to  humans-ss24@vision.in.tum.de

Description

In this seminar, we are taking a brief glimpse at some of the very recent works conducted in the area of human motion analysis and generation. We would discuss various research directions such as 4D reconstruction and novel view synthesis, human pose estimation and moti…</summary>
    </entry>
    <entry>
        <title>Seminar: Neural Network Design Patterns in Computer Vision (5 ECTS)</title>
        <link rel="alternate" type="text/html" href="https://cvg.cit.tum.de/teaching/ss2024/patterns?rev=1726126184&amp;do=diff"/>
        <published>2024-09-12T07:29:44+00:00</published>
        <updated>2024-09-12T07:29:44+00:00</updated>
        <id>https://cvg.cit.tum.de/teaching/ss2024/patterns?rev=1726126184&amp;do=diff</id>
        <author>
            <name>Anonymous</name>
            <email>anonymous@undisclosed.example.com</email>
        </author>
        <category  term="teaching:ss2024" />
        <content>----------

Seminar: Neural Network Design Patterns in Computer Vision (5 ECTS)

 Summer Semester 2024, TU München 

Organiser: 
Roman Pflugfelder

Description

Computer vision considers models of neural networks initially invented by the machine learning community. This seminar allows the student to study neural networks in more detail. By the end of the seminar, all participants will understand the principles and the applications of selected models, and they will receive the ability to reuse t…</content>
        <summary>----------

Seminar: Neural Network Design Patterns in Computer Vision (5 ECTS)

 Summer Semester 2024, TU München 

Organiser: 
Roman Pflugfelder

Description

Computer vision considers models of neural networks initially invented by the machine learning community. This seminar allows the student to study neural networks in more detail. By the end of the seminar, all participants will understand the principles and the applications of selected models, and they will receive the ability to reuse t…</summary>
    </entry>
    <entry>
        <title>Practical Course: Vision-based Navigation IN2106 (6h SWS / 10 ECTS)</title>
        <link rel="alternate" type="text/html" href="https://cvg.cit.tum.de/teaching/ss2024/visnav_ss2024?rev=1713359702&amp;do=diff"/>
        <published>2024-04-17T13:15:02+00:00</published>
        <updated>2024-04-17T13:15:02+00:00</updated>
        <id>https://cvg.cit.tum.de/teaching/ss2024/visnav_ss2024?rev=1713359702&amp;do=diff</id>
        <author>
            <name>Anonymous</name>
            <email>anonymous@undisclosed.example.com</email>
        </author>
        <category  term="teaching:ss2024" />
        <content>Practical Course: Vision-based Navigation IN2106 (6h SWS / 10 ECTS)

SS 2024, TU München

Lecturers:  Sergei Solonets,  Daniil Synitsin

Please direct questions to &lt;visnav-ss24@vision.in.tum.de&gt;

News

No session on 08.05!!!

The pre-meeting will be held on Zoom 07.02 at 14:00
&lt;https://tum-conf.zoom-x.de/j/66945147179?pwd=UE5teFZOSEJKZXBTb3VYWlRzZVdqZz09&gt;

[premeeting slides (ss24)] have been uploaded

[premeeting slides with potential projects (ss24)] have been uploaded</content>
        <summary>Practical Course: Vision-based Navigation IN2106 (6h SWS / 10 ECTS)

SS 2024, TU München

Lecturers:  Sergei Solonets,  Daniil Synitsin

Please direct questions to &lt;visnav-ss24@vision.in.tum.de&gt;

News

No session on 08.05!!!

The pre-meeting will be held on Zoom 07.02 at 14:00
&lt;https://tum-conf.zoom-x.de/j/66945147179?pwd=UE5teFZOSEJKZXBTb3VYWlRzZVdqZz09&gt;

[premeeting slides (ss24)] have been uploaded

[premeeting slides with potential projects (ss24)] have been uploaded</summary>
    </entry>
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