Home  | News

22.01.2024

Teaser image to The MCML-Exhibition at Deutsches Museum Munich

The MCML-Exhibition at Deutsches Museum Munich

Our Exhibition Was a Great Success - A Short Recap

The Science Communication Lab at Deutsches Museum hosted our MCML exhibition that attracted thousands of visitors over three weeks.

The exhibition featured interactive exhibits on machine learning, simultaneous localization and mapping (SLAM), and Stable Diffusion, an algorithm that connects images and text. Visitors gained insights into cutting-edge research and enjoyed engaging hands-on experiences.

Around 1.000 visitors per day passed by the Science Communication Lab at Deutsches Museum and saw our exhibition during the last three weeks. It was a lot of fun and we are happy that so many visitors were interested and got a glimpse of our research.

One of the exhibits called AMELIE taught visitors the basics of machine learning in a fun and interactive way. The exhibit was built by the LMU Media Informatics Group of our PI Albrecht Schmidt. You can see a video of the exhibit on YouTube.

Watch AMELIE on youtube

In addition we had a demo showing how it is possible to simultaneously do localization and mapping of the environment using a camera and an attached IMU sensor. The method is called DM-VIO and can be used in self-driving cars, for example. DM-VIO is a project of the TUM Computer Vision Group led by our director Daniel Cremers.

Last but not least, we gave some insights into Stable Diffusion, a deep learning model that generates images from text descriptions. Stable Diffusion is developed by the LMU Computer Vision & Learning Group of our PI Björn Ommer. We explained how Stable Diffusion learns the connection between image and text through a latent diffusion model process.


Poster 1

Poster 1: How does AI learn

AMELIE is the name of the museum exhibit that helped visitors understand machine learning principles.

Poster 2

Poster 2: Reconstructing the world with AI

We presented DM-VIO, a monocular visual-inertial odometry system based on two novel techniques called delayed marginalization and pose graph bundle adjustment.

Poster 3

Poster 3: DM-VIO demo

On this poster visitors saw how the Simultaneous Localization and Mapping unfolds

Poster 4

Poster 4: Image generation using AI

Visitors saw how Stable Diffusion works and were able to try it out themselves.


#event #research
Subscribe to RSS News feed

Related

Link to Zigzag Your Way to Faster, Smarter AI Image Generation

20.11.2025

Zigzag Your Way to Faster, Smarter AI Image Generation

ZigMa, introduced by Björn Ommer’s group at ECCV 24, improves high-res AI image and video generation with fast, memory-efficient zigzag scanning.

Link to Anne-Laure Boulesteix Among the World’s Most Cited Researchers

13.11.2025

Anne-Laure Boulesteix Among the World’s Most Cited Researchers

MCML PI Anne‑Laure Boulesteix named Highly Cited Researcher 2025 for cross-field work, among 17 LMU scholars recognized globally.

Link to Björn Ommer Featured in Frankfurter Rundschau

13.11.2025

Björn Ommer Featured in Frankfurter Rundschau

Björn Ommer highlights how Google’s new AI search mode impacts publishers, content visibility, and the diversity of online information.

Link to Fabian Theis Among the World’s Most Cited Researchers

13.11.2025

Fabian Theis Among the World’s Most Cited Researchers

Fabian Theis is named a Highly Cited Researcher 2025 for his work in mathematical modeling of biological systems.

Link to Explaining AI Decisions: Shapley Values Enable Smart Exosuits

13.11.2025

Explaining AI Decisions: Shapley Values Enable Smart Exosuits

AI meets wearable robotics: MCML and Harvard researchers make exosuits smarter and safer with explainable optimization, presented at ECML-PKDD 2025.

Back to Top