The Mapillary Traffic Sign Dataset for Detection and Classification on a Global Scale

no code implementations • ECCV 2020 • Christian Ertler, Jerneja Mislej, Tobias Ollmann, Lorenzo Porzi, Gerhard Neuhold, Yubin Kuang

In this paper, we introduce a traffic sign benchmark dataset of 100K street-level images around the world that encapsulates diverse scenes, wide coverage of geographical locations, and varying weather and lighting conditions and covers more than 300 manually annotated traffic sign classes.

Autonomous Driving Classification +3

The Mapillary Vistas Dataset for Semantic Understanding of Street Scenes

no code implementations • ICCV 2017 • Gerhard Neuhold, Tobias Ollmann, Samuel Rota Bulo, Peter Kontschieder

The Mapillary Vistas Dataset is a novel, large-scale street-level image dataset containing 25, 000 high-resolution images annotated into 66 object categories with additional, instance-specific labels for 37 classes.

Image Segmentation Instance Segmentation +3

Loss Max-Pooling for Semantic Image Segmentation

no code implementations • CVPR 2017 • Samuel Rota Bulò, Gerhard Neuhold, Peter Kontschieder

We introduce a novel loss max-pooling concept for handling imbalanced training data distributions, applicable as alternative loss layer in the context of deep neural networks for semantic image segmentation.

Image Segmentation Segmentation +1