5 papers · 1 filter
Simultaneous Semantic Segmentation and Outlier Detection in Presence of Domain Shift
Petra Bevandić, Ivan Krešo, Marin Oršić +1
Recent success on realistic road driving datasets has increased interest in exploring robust performance in real-world applications. One of the major unsolved problems is to identi…
Efficient Ladder-style DenseNets for Semantic Segmentation of Large Images
Ivan Krešo, Josip Krapac, Siniša Šegvić
Recent progress of deep image classification models has provided great potential to improve state-of-the-art performance in related computer vision tasks. However, the transition t…
In Defense of Pre-trained ImageNet Architectures for Real-time Semantic Segmentation of Road-driving Images
Marin Oršić, Ivan Krešo, Petra Bevandić +1
Recent success of semantic segmentation approaches on demanding road driving datasets has spurred interest in many related application fields. Many of these applications involve re…
Discriminative out-of-distribution detection for semantic segmentation
Petra Bevandić, Ivan Krešo, Marin Oršić +1
Most classification and segmentation datasets assume a closed-world scenario in which predictions are expressed as distribution over a predetermined set of visual classes. However,…
Robust Semantic Segmentation with Ladder-DenseNet Models
Ivan Krešo, Marin Oršić, Petra Bevandić +1
We present semantic segmentation experiments with a model capable to perform predictions on four benchmark datasets: Cityscapes, ScanNet, WildDash and KITTI. We employ a ladder-sty…