176 citations · 274 across the 36 of their papers we have counts for
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A Domain Agnostic Normalization Layer for Unsupervised Adversarial Domain Adaptation
Rob Romijnders, Panagiotis Meletis, Gijs Dubbelman
We propose a normalization layer for unsupervised domain adaption in semantic scene segmentation. Normalization layers are known to improve convergence and generalization and are p…
Panoptic Segmentation with a Joint Semantic and Instance Segmentation Network
Daan de Geus, Panagiotis Meletis, Gijs Dubbelman
We present a single network method for panoptic segmentation. This method combines the predictions from a jointly trained semantic and instance segmentation network using heuristic…
Monocular Semantic Occupancy Grid Mapping with Convolutional Variational Encoder-Decoder Networks
Chenyang Lu, Marinus Jacobus Gerardus van de Molengraft, Gijs Dubbelman
In this work, we research and evaluate end-to-end learning of monocular semantic-metric occupancy grid mapping from weak binocular ground truth. The network learns to predict four…
An Experimental Study on Relative and Absolute Pose Graph Fusion for Vehicle Localization
Anweshan Das, Gijs Dubbelman
In this work, we research and evaluate multiple pose-graph fusion strategies for vehicle localization. We focus on fusing a single absolute localization system, i.e. automotive-gra…
Training of Convolutional Networks on Multiple Heterogeneous Datasets for Street Scene Semantic Segmentation
Panagiotis Meletis, Gijs Dubbelman
We propose a convolutional network with hierarchical classifiers for per-pixel semantic segmentation, which is able to be trained on multiple, heterogeneous datasets and exploit th…