Shallow models meet deep vision

Project Details


This project is concerned with perceiving, understanding, and representing objects and their environment. This constitutes key challenges for any autonomous system or augmented reality setup, especially when these functions are performed under uncertainty. The project combines statistical machine learning and computer vision to develop new methods for data-driven 3D visual computing, uncertainty quantification, and online learning. We put special interest in advancing the state-of-the-art in vision and sensor fusion methods, and in developing methods capable of inferring location, pose, and semantics from visual data under uncertainty. This is a crossover of the fields of computer vision and statistical machine learning, and aim at renewing the view on how the two can be combined.
Effective start/end date01/09/201931/08/2023

Collaborative partners

UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):

  • SDG 13 - Climate Action


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