Master Thesis Open-World 3D Anomaly Segmentation with Vision-Language Models (f/m/x)

Bayerische Motoren Werke Aktiengesellschaft; München; Vor Ort; EUR 30.000 - 50.000; Vollzeit

Zusammenfassung

Ein innovatives Unternehmen sucht leidenschaftliche Studierende für eine Masterarbeit im Bereich der offenen 3D-Anomalie-Segmentierung. Diese spannende Gelegenheit bietet die Möglichkeit, mit fortschrittlichen Vision-Language-Modellen zu arbeiten und neuartige Ansätze zur Segmentierung in 3D-Umgebungen zu entwickeln. Sie werden Teil eines dynamischen Teams, das Sie von Anfang an unterstützt und ermutigt, Ihre Ideen einzubringen. Nutzen Sie die Chance, Ihre Fähigkeiten in einem zukunftsorientierten Umfeld zu zeigen und einen echten Einfluss auf die Technologie von morgen zu haben. Wenn Sie bereit sind, Ihre Kenntnisse in Deep Learning und Computer Vision einzusetzen, freuen wir uns auf Ihre Bewerbung.

Leistungen

Digitale Angebote & mobiles Arbeiten

Attraktive Vergütung

Wohnungsangebote für Studierende

Qualifikationen

• Starkes Fundament in Deep Learning und Computer Vision erforderlich.
• Vorherige Erfahrungen mit Vision-Language-Modellen sind von Vorteil.

Aufgaben

• Entwicklung neuartiger Methoden zur Generierung von 3D-Semantikanalysen.
• Evaluierung von Open-Vocabulary 2D-Segmentierung für 3D-Segmentierung.

Kenntnisse

Deep Learning

Computer Vision

Vision-Language Models

Anomaly Detection

Semantic Segmentation

Ausbildung

Master's Degree in Computer Science or related field

Tools

Open World 3D Dataset

Jobbeschreibung

Master Thesis Open-World 3D Anomaly Segmentation with Vision-Language Models (f/m/x)

THE BEST INTERNSHIP IN THEORY - AND IN PRACTICE.

SHARE YOUR PASSION.

World-leading technologies don’t make it into a BMW until they’ve undergone one of the most challenging journeys imaginable. It takes dynamic teams with outstanding technical skills to take them from the drawing board to the road. That’s why our experts will treat you as part of the team from day one, encourage you to bring your own ideas to the table – and give you the opportunity to really show what you can do.

We, the BMW Group, offer you an interesting and varied Master thesis in the field of open-world 3D anomaly segmentation, focusing on leveraging contrastive vision-language models to understand and segment unknown objects in 3D environments. This project will utilize the Open World 3D dataset, which provides both 3D bounding boxes and 2D image data, enabling innovative multi-modal segmentation approaches.

What awaits you?

• Vision-language models for open-world perception.
• Pseudo-labeling techniques with segmentation models.
• Anomaly detection through contrastive feature representations.
• Develop novel methods to generate 3D semantic segmentation data from existing annotations.
• Evaluate open-vocabulary 2D segmentation as a foundation for 3D segmentation.
• Compare various feature representations, including BEV-based heatmaps, for improved segmentation.

This thesis will be supervised by a professor at Technical University of Munich (TUM). Please note that your thesis must be supervised by a university on your part.

What should you bring along?

• Students with a strong background in deep learning and computer vision.
• Ideally be enrolled at TUM.
• Prior experience with vision-language models, multi-view projection or semantic segmentation is a plus but not mandatory.

If you are passionate about advancing open-world 3D anomaly segmentation and working with cutting-edge vision-language models, we look forward to your application!

What do we offer?

• Digital offers & mobile working.
• Attractive remuneration.
• Apartment offers for students (subject to availability & only Munich).

Do you have any questions? Then simply send your enquiry using our contact form. Your enquiry will then be answered by telephone or e-mail.

At the BMW Group, we see diversity and inclusion in all its dimensions as a strength for our teams. Equal opportunities are a particular concern for us, and the equal treatment of applicants and employees is a fundamental principle of our corporate policy. That is why our recruiting decisions are also based on personality, experience and skills.