3 papers
cs.CV2021
4D Panoptic LiDAR Segmentation
Mehmet Aygün, Aljoša Ošep, Mark Weber +4
Temporal semantic scene understanding is critical for self-driving cars or robots operating in dynamic environments. In this paper, we propose 4D panoptic LiDAR segmentation to ass…
cs.CV2020
Unsupervised Dense Shape Correspondence using Heat Kernels
Mehmet Aygün, Zorah Lähner, Daniel Cremers
In this work, we propose an unsupervised method for learning dense correspondences between shapes using a recent deep functional map framework. Instead of depending on ground-truth…
cs.CV2018
Multi Modal Convolutional Neural Networks for Brain Tumor Segmentation
Mehmet Aygün, Yusuf Hüseyin Şahin, Gözde Ünal
In this work, we propose a multi-modal Convolutional Neural Network (CNN) approach for brain tumor segmentation. We investigate how to combine different modalities efficiently in t…