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    <title>Computer Vision Group teaching:ws2025</title>
    <subtitle></subtitle>
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    <updated>2026-04-22T22:15:48+00:00</updated>
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    <entry>
        <title>Master Seminar - Recent Advances in 4D Computer Vision (5 ECTS)</title>
        <link rel="alternate" type="text/html" href="https://cvg.cit.tum.de/teaching/ws2025/4d-vision?rev=1752586192&amp;do=diff"/>
        <published>2025-07-15T13:29:52+00:00</published>
        <updated>2025-07-15T13:29:52+00:00</updated>
        <id>https://cvg.cit.tum.de/teaching/ws2025/4d-vision?rev=1752586192&amp;do=diff</id>
        <author>
            <name>Anonymous</name>
            <email>anonymous@undisclosed.example.com</email>
        </author>
        <category  term="teaching:ws2025" />
        <content>----------

Master Seminar - Recent Advances in 4D Computer Vision (5 ECTS)

 Winter Semester 2025/26, TU München 

Organisers: 
Cecilia Curreli, Mariia Gladkova

Please direct all questions to  4dvision-ws25@vision.in.tum.de.

Description

In this seminar, we will delve into the forefront of computer vision, focusing on the latest deep lea</content>
        <summary>----------

Master Seminar - Recent Advances in 4D Computer Vision (5 ECTS)

 Winter Semester 2025/26, TU München 

Organisers: 
Cecilia Curreli, Mariia Gladkova

Please direct all questions to  4dvision-ws25@vision.in.tum.de.

Description

In this seminar, we will delve into the forefront of computer vision, focusing on the latest deep lea</summary>
    </entry>
    <entry>
        <title>Computer Vision III: Detection, Segmentation and Tracking (IN2375)</title>
        <link rel="alternate" type="text/html" href="https://cvg.cit.tum.de/teaching/ws2025/cv3?rev=1758788725&amp;do=diff"/>
        <published>2025-09-25T08:25:25+00:00</published>
        <updated>2025-09-25T08:25:25+00:00</updated>
        <id>https://cvg.cit.tum.de/teaching/ws2025/cv3?rev=1758788725&amp;do=diff</id>
        <author>
            <name>Anonymous</name>
            <email>anonymous@undisclosed.example.com</email>
        </author>
        <category  term="teaching:ws2025" />
        <content>----------

Computer Vision III: Detection, Segmentation and Tracking (IN2375)

Overview

Computer Vision III offers a comprehensive review of methods for high-level computer vision tasks: object detection, image segmentation and object tracking.
These tasks are one of the most compelling applications of computer vision in the real world.
Research on these applications is still very active and highly impactful in computer vision.
The material of this course spans the recent literature leveraging…</content>
        <summary>----------

Computer Vision III: Detection, Segmentation and Tracking (IN2375)

Overview

Computer Vision III offers a comprehensive review of methods for high-level computer vision tasks: object detection, image segmentation and object tracking.
These tasks are one of the most compelling applications of computer vision in the real world.
Research on these applications is still very active and highly impactful in computer vision.
The material of this course spans the recent literature leveraging…</summary>
    </entry>
    <entry>
        <title>Seminar: Selected Topics in Deep Learning -- Equivariance &amp; Dynamics (5 ECTS)</title>
        <link rel="alternate" type="text/html" href="https://cvg.cit.tum.de/teaching/ws2025/dl-equi-dynam?rev=1776067064&amp;do=diff"/>
        <published>2026-04-13T07:57:44+00:00</published>
        <updated>2026-04-13T07:57:44+00:00</updated>
        <id>https://cvg.cit.tum.de/teaching/ws2025/dl-equi-dynam?rev=1776067064&amp;do=diff</id>
        <author>
            <name>Anonymous</name>
            <email>anonymous@undisclosed.example.com</email>
        </author>
        <category  term="teaching:ws2025" />
        <content>----------

Seminar: Selected Topics in Deep Learning -- Equivariance &amp; Dynamics (5 ECTS)

 Winter Semester 2025

Organizer: 
Karnik Ram (karnik.ram@tum.de)

 Preliminary meeting : 11.07.25. 14:00 - 14:30 CET. Slides

Description

The current trend in deep learning is towards scaling model size and data, and more recently test-time compute. A smaller but steady trend has been in introducing certain physics-inspired inductive biases such as symmetries and dynamics into these models. Apart from be…</content>
        <summary>----------

Seminar: Selected Topics in Deep Learning -- Equivariance &amp; Dynamics (5 ECTS)

 Winter Semester 2025

Organizer: 
Karnik Ram (karnik.ram@tum.de)

 Preliminary meeting : 11.07.25. 14:00 - 14:30 CET. Slides

Description

The current trend in deep learning is towards scaling model size and data, and more recently test-time compute. A smaller but steady trend has been in introducing certain physics-inspired inductive biases such as symmetries and dynamics into these models. Apart from be…</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/ws2025/graph_learning_ws25?rev=1762246717&amp;do=diff"/>
        <published>2025-11-04T08:58:37+00:00</published>
        <updated>2025-11-04T08:58:37+00:00</updated>
        <id>https://cvg.cit.tum.de/teaching/ws2025/graph_learning_ws25?rev=1762246717&amp;do=diff</id>
        <author>
            <name>Anonymous</name>
            <email>anonymous@undisclosed.example.com</email>
        </author>
        <category  term="teaching:ws2025" />
        <content>Seminar: Advanced topics in Graph Learning (5 ECTS)

Winter Semester 2025, 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)

Winter Semester 2025, 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: Neural Network Design Patterns in Computer Vision (5 ECTS)</title>
        <link rel="alternate" type="text/html" href="https://cvg.cit.tum.de/teaching/ws2025/patterns?rev=1755691824&amp;do=diff"/>
        <published>2025-08-20T12:10:24+00:00</published>
        <updated>2025-08-20T12:10:24+00:00</updated>
        <id>https://cvg.cit.tum.de/teaching/ws2025/patterns?rev=1755691824&amp;do=diff</id>
        <author>
            <name>Anonymous</name>
            <email>anonymous@undisclosed.example.com</email>
        </author>
        <category  term="teaching:ws2025" />
        <content>----------

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

 Winter Semester 2025, 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)

 Winter Semester 2025, 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: 3D Shape Analysis and Virtual Humans Applications (10ECTS)</title>
        <link rel="alternate" type="text/html" href="https://cvg.cit.tum.de/teaching/ws2025/savha?rev=1753172036&amp;do=diff"/>
        <published>2025-07-22T08:13:56+00:00</published>
        <updated>2025-07-22T08:13:56+00:00</updated>
        <id>https://cvg.cit.tum.de/teaching/ws2025/savha?rev=1753172036&amp;do=diff</id>
        <author>
            <name>Anonymous</name>
            <email>anonymous@undisclosed.example.com</email>
        </author>
        <category  term="teaching:ws2025" />
        <content>Practical Course: 3D Shape Analysis and Virtual Humans Applications (10ECTS)

 Winter Semester 2025/2026, TU München 

Organisers: 
Viktoria Ehm, Maolin Gao, Dr. Riccardo Marin, Thomas Dages

 Contact :
savha-ss25@vision.in.tum.de

News

	*  22.7.2025 Preliminary meeting slides are available</content>
        <summary>Practical Course: 3D Shape Analysis and Virtual Humans Applications (10ECTS)

 Winter Semester 2025/2026, TU München 

Organisers: 
Viktoria Ehm, Maolin Gao, Dr. Riccardo Marin, Thomas Dages

 Contact :
savha-ss25@vision.in.tum.de

News

	*  22.7.2025 Preliminary meeting slides are available</summary>
    </entry>
    <entry>
        <title>Master Seminar - 3D Vision Foundation Models</title>
        <link rel="alternate" type="text/html" href="https://cvg.cit.tum.de/teaching/ws2025/seminar_3dvfm?rev=1751911731&amp;do=diff"/>
        <published>2025-07-07T18:08:51+00:00</published>
        <updated>2025-07-07T18:08:51+00:00</updated>
        <id>https://cvg.cit.tum.de/teaching/ws2025/seminar_3dvfm?rev=1751911731&amp;do=diff</id>
        <author>
            <name>Anonymous</name>
            <email>anonymous@undisclosed.example.com</email>
        </author>
        <category  term="teaching:ws2025" />
        <content>Master Seminar - 3D Vision Foundation Models

 Winter Semester 2025/26, TU München 

Organisers: 
Shenhan Qian, Linus Härenstam-Nielsen, Ganlin Zhang, Weirong Chen

Email: 3dvfm-mm3dr-ws25@vision.in.tum.de

Description

This seminar examines the rise of foundation models for 3D vision, focusing on their architectures, training paradigms, and downstream applications. Core topics include models like DUST3R and VGGT, as well as related approaches that aim for generalizable 3D understanding across t…</content>
        <summary>Master Seminar - 3D Vision Foundation Models

 Winter Semester 2025/26, TU München 

Organisers: 
Shenhan Qian, Linus Härenstam-Nielsen, Ganlin Zhang, Weirong Chen

Email: 3dvfm-mm3dr-ws25@vision.in.tum.de

Description

This seminar examines the rise of foundation models for 3D vision, focusing on their architectures, training paradigms, and downstream applications. Core topics include models like DUST3R and VGGT, as well as related approaches that aim for generalizable 3D understanding across t…</summary>
    </entry>
    <entry>
        <title>Master Seminar - Modern Methods for 3D Representation and Reconstruction</title>
        <link rel="alternate" type="text/html" href="https://cvg.cit.tum.de/teaching/ws2025/seminar_mm3dr?rev=1751911744&amp;do=diff"/>
        <published>2025-07-07T18:09:04+00:00</published>
        <updated>2025-07-07T18:09:04+00:00</updated>
        <id>https://cvg.cit.tum.de/teaching/ws2025/seminar_mm3dr?rev=1751911744&amp;do=diff</id>
        <author>
            <name>Anonymous</name>
            <email>anonymous@undisclosed.example.com</email>
        </author>
        <category  term="teaching:ws2025" />
        <content>Master Seminar - Modern Methods for 3D Representation and Reconstruction

 Winter Semester 2025/26, TU München 

Organisers: 
Shenhan Qian, Linus Härenstam-Nielsen, Ganlin Zhang, Weirong Chen

Email: 3dvfm-mm3dr-ws25@vision.in.tum.de

Description

This seminar explores contemporary techniques for reconstructing 3D geometry from images, with a focus on learning-based and hybrid approaches. Topics include Neural Radiance Fields (NeRF), 3D Gaussian Splatting (3DGS), Signed Distance Functions (SDFs)…</content>
        <summary>Master Seminar - Modern Methods for 3D Representation and Reconstruction

 Winter Semester 2025/26, TU München 

Organisers: 
Shenhan Qian, Linus Härenstam-Nielsen, Ganlin Zhang, Weirong Chen

Email: 3dvfm-mm3dr-ws25@vision.in.tum.de

Description

This seminar explores contemporary techniques for reconstructing 3D geometry from images, with a focus on learning-based and hybrid approaches. Topics include Neural Radiance Fields (NeRF), 3D Gaussian Splatting (3DGS), Signed Distance Functions (SDFs)…</summary>
    </entry>
    <entry>
        <title>Seminar: Modern Methods for 3D Reconstruction and Representation</title>
        <link rel="alternate" type="text/html" href="https://cvg.cit.tum.de/teaching/ws2025/seminar_modern3d?rev=1739439972&amp;do=diff"/>
        <published>2025-02-13T09:46:12+00:00</published>
        <updated>2025-02-13T09:46:12+00:00</updated>
        <id>https://cvg.cit.tum.de/teaching/ws2025/seminar_modern3d?rev=1739439972&amp;do=diff</id>
        <author>
            <name>Anonymous</name>
            <email>anonymous@undisclosed.example.com</email>
        </author>
        <category  term="teaching:ws2025" />
        <content>----------

Seminar: Modern Methods for 3D Reconstruction and Representation

Seminar IN2107, which is open to Master students from &quot;computer science&quot;, &quot;games engineering&quot;, &quot;robotics, cognition, and intelligence&quot;, and other programs. Please consult TUMonline or your study coordinator for more information.</content>
        <summary>----------

Seminar: Modern Methods for 3D Reconstruction and Representation

Seminar IN2107, which is open to Master students from &quot;computer science&quot;, &quot;games engineering&quot;, &quot;robotics, cognition, and intelligence&quot;, and other programs. Please consult TUMonline or your study coordinator for more information.</summary>
    </entry>
    <entry>
        <title>Seminar: Unsupervised Learning in Computer Vision (5 ECTS)</title>
        <link rel="alternate" type="text/html" href="https://cvg.cit.tum.de/teaching/ws2025/ulcv?rev=1775036679&amp;do=diff"/>
        <published>2026-04-01T09:44:39+00:00</published>
        <updated>2026-04-01T09:44:39+00:00</updated>
        <id>https://cvg.cit.tum.de/teaching/ws2025/ulcv?rev=1775036679&amp;do=diff</id>
        <author>
            <name>Anonymous</name>
            <email>anonymous@undisclosed.example.com</email>
        </author>
        <category  term="teaching:ws2025" />
        <content>----------

Seminar: Unsupervised Learning in Computer Vision (5 ECTS)

 Winter Semester 2025/26, TU München 

Organisers: 
Dominik Schnaus, Christoph Reich

Please direct questions to &lt;ulcv-ws25@vision.in.tum.de&gt;

News

01.04.2026: Report Friendly reminder, report submission deadline is tomorrow (02.04.2026) by the end of the day. Please send your report to</content>
        <summary>----------

Seminar: Unsupervised Learning in Computer Vision (5 ECTS)

 Winter Semester 2025/26, TU München 

Organisers: 
Dominik Schnaus, Christoph Reich

Please direct questions to &lt;ulcv-ws25@vision.in.tum.de&gt;

News

01.04.2026: Report Friendly reminder, report submission deadline is tomorrow (02.04.2026) by the end of the day. Please send your report to</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/ws2025/visnav_ws2025?rev=1759762437&amp;do=diff"/>
        <published>2025-10-06T14:53:57+00:00</published>
        <updated>2025-10-06T14:53:57+00:00</updated>
        <id>https://cvg.cit.tum.de/teaching/ws2025/visnav_ws2025?rev=1759762437&amp;do=diff</id>
        <author>
            <name>Anonymous</name>
            <email>anonymous@undisclosed.example.com</email>
        </author>
        <category  term="teaching:ws2025" />
        <content>Practical Course: Vision-based Navigation IN2106 (6h SWS / 10 ECTS)

WS 2025, TU München

Lecturers:  Jason Chui,  Mateo de Mayo,  Jonathan Eichhorn

Please direct questions to &lt;visnav-ws25@vision.in.tum.de&gt;.

News

	*  For the first class on October 13th we have just one hour due to the Welcome@TUM event. Please be on time.</content>
        <summary>Practical Course: Vision-based Navigation IN2106 (6h SWS / 10 ECTS)

WS 2025, TU München

Lecturers:  Jason Chui,  Mateo de Mayo,  Jonathan Eichhorn

Please direct questions to &lt;visnav-ws25@vision.in.tum.de&gt;.

News

	*  For the first class on October 13th we have just one hour due to the Welcome@TUM event. Please be on time.</summary>
    </entry>
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