Deep Learning + Software Engineering: Effect of noisy map labels on the map perception task

Forschungsthema/Bereich

Deep Learning in Autonomous Driving

Typ der Abschlussarbeit

Bachelor / Master

Startzeitpunkt

-

Bewerbungsschluss

01.08.2025

Dauer der Arbeit

3 - 8 Monate

Beschreibung

Current state-of-the-art map construction methods such as MapTRv2 use sensor data (360° surround view camera setup and LiDAR) to construct high definition maps.
These methods extract features from the sensor data and transform them into a Bird's Eye View (BEV) representation and derive maps in polyline representation using transformer-based architectures.
However, the construction of high quality maps requires accurate labels, but due to road construction or human error in labeling, the quality can not always guaranteed.

The goal of this thesis is to investigate the effect of map label noise on the performance of map construction models.
Therefore, different types of map label noise should be implemented in the label generation process of the dataset Argoverse 2 (https://www.argoverse.org/av2.html).
Afterwards the map construction model MapTRv2 should be trained with noisy labels and the performance evaluated on a validation dataset without map label noise.

Voraussetzung

Voraussetzungen an Studierende

• Knowledge in Python, PyTorch and Deep Learning
• Knowledge in Linux and Maps is a plus
• Independent working style and interest in learning new things

Studiengangsbereiche

• Ingenieurwissenschaften
  Elektrotechnik & Informationstechnik
  Informatik
  Maschinenbau
  Mechatronik & Informationstechnik
  Mechanical Engineering

Betreuung

Titel, Vorname, Name

Jonas, Merkert

Organisationseinheit

Institut für Mess- und Regelungstechnik

E-Mail Adresse

jonas.merkert@kit.edu

Link zur eigenen Homepage/Personenseite

Website

Bewerbung per E-Mail

Bewerbungsunterlagen

• Lebenslauf
• Notenauszug
• Immatrikulationsbescheinigung

E-Mail Adresse für die Bewerbung
Senden Sie die oben genannten Bewerbungsunterlagen bitte per Mail an jonas.merkert@kit.edu


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