Munich AI, Machine Learning and Computer Vision Meetup
Nov 20, 2024 | 5:30 to 8:30 PM
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Date, Time and Location
Date and Time
Nov 20, 2024 from 5:30 PM to 8:30 PM
Location
The Meetup will take place at Macromedia University, Auditorium 608 in Munich
Robust and Efficient Coupling of Perception to Actuation with Metric and Non-Metric Scene Representations
Prof. Darius Burschka
Technical University of Munich
We will present our work on robust and efficient ways, how camera information can be used to control an autonomous car. While many metric approaches require repeated intrinsic (sensor itself) and extrinsic (position of the sensor in the vehicle), our methods allow a direct control of the system solving the control problem directly in the retina (image plane) of the sensor. We will discuss the rich information encoded in the geometric projection of the scene that can be used for accurate navigation that includes uncertainty information necessary for fusion of diverse sensors and a novel way, how the dynamic information can be represented in the scene for planning in dynamic environments.
About the Speaker
Prof. Burschka of the Technical University of Munich conducts research into sensor systems in robotics and human-machine interfaces. Video-based navigation is one of his particular interests. This involves simulation of complex sensor systems through the analysis and fusion of sensor properties of physical sensor units and 3D reconstruction from the fusion of multimodal sensor data.
Strategies Towards Reliable Scene Understanding for Autonomous Driving and Beyond
Stefano Gasperini
Co-Founder & CEO at VisualAIs and Researcher at TUM
Scene understanding is crucial for self-driving cars and autonomous agents to reliably perceive their surroundings in diverse, unpredictable conditions. This talk tackles these challenges by presenting a series of research papers that improve reliability through novel methods in 2D and 3D perception, focusing on robustness in extreme scenarios and generalization to unseen environments.
About the Speaker
Stefano Gasperini is the Co-Founder & CEO of Visualais, a Computer Vision startup enabling the creation of 3D renderings from smartphone images. Beyond numerous top-tier research papers and outstanding reviewer awards from his PhD at TUM, as PostDoc, Stefano keeps contributing to Computer Vision and AI by advising a team of PhD students at TUM.
How to Unlock More Value from Self-Driving Datasets
Dan Gural
Machine learning Engineer at Voxel51
AV/ADAS is one of the most advanced fields in Visual AI. However, getting your hands on a high quality dataset can be tough, let alone working with them to get a model to production. In this talk, I will show you the leading methods and tools to help visualize as well take these datasets to the next level. I will demonstrate how to clean and curate AV datasets as well as perform state of the art augmentations using diffusion models to create synthetic data that can empower the self driving car models of the future,
About the Speaker
Daniel Gural is a seasoned Machine Learning Engineer at Voxel51 with a strong passion for empowering Data Scientists and ML Engineers to unlock the full potential of their data.
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The goal of the AI, Machine Learning, and Computer Vision Meetup network is to bring together a community of data scientists, machine learning engineers, and open source enthusiasts who want to share and expand their knowledge of AI and complementary technologies. If that’s you, we invite you to join the Meetup closest to your timezone.
