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Mathias Ortner

2 accepted papers

2023

Enhanced GM-PHD Filter for Real Time Satellite Multi-Target Tracking

ICASSP 2023accepted

We present a real-time multi-object tracker using an enhanced version of the Gaussian mixture probability hypothesis density (GM-PHD) filter to track detections of a state-of-the-art convolutional neural network (CNN). This approach adapts the GM-PHD filter to a real-world scenario to recover target…

Cited by 1SourceScholar
2020

Learning Disentangled Representations via Mutual Information Estimation

ECCV 2020poster

In this paper, we investigate the problem of learning disentangled representations. Given a pair of images sharing some attributes, we aim to create a low-dimensional representation which is split into two parts: a shared representation that captures the common information between the images and an…