One Computer Science MSc thesis to be presented on 24 January

Friday, 24 January there will be a master thesis presentation in Computer Science at Lund University, Faculty of Engineering.

The presentation will take place in E:1406.

Note to potential opponents: Register as an opponent to the presentation of your choice by sending an email to the examiner for that presentation (firstname.lastname@cs.lth.se). Do not forget to specify the presentation you register for! Note that the number of opponents may be limited (often to two), so you might be forced to choose another presentation if you register too late. Registrations are individual, just as the oppositions are! More instructions are found on this page.

15:15-16:00 in E:1406 and in Zoom (see link below)

Presenters: Ludvig Delvret, Theodor Lundqvist
Title: GeoJEPA: Towards Eliminating Augmentation- and Sampling Bias in Multimodal Geospatial Learning
Examiner: Björn Regnell
Supervisor: Jonas Skeppstedt (LTH)

Existing methods for self-supervised representation learning of geospatial regions and map entities rely extensively on the design of pretext tasks, often involving augmentations or heuristic sampling of positive and negative pairs based on spatial proximity. This reliance introduces biases and limits the representations' expressiveness and generalisability. Consequently, the literature has expressed a pressing need to explore different methods for modelling geospatial data.

To address the key difficulties of such methods, namely multimodality, heterogeneity, and the choice of pretext tasks, we present GeoJEPA, a versatile multimodal fusion model for geospatial data built on the self-supervised Joint-Embedding Predictive Architecture. With GeoJEPA, we aim to eliminate the widely accepted augmentation- and sampling biases found in self-supervised geospatial representation learning. GeoJEPA uses self-supervised pretraining on a large dataset of OpenStreetMap attributes, geometries and aerial images. The results are multimodal semantic representations of urban regions and map entities that we evaluate both quantitatively and qualitatively.

Link to popular science summary: To be uploaded

Link to Zoom presentation: https://lu-se.zoom.us/j/69456288546