Iterative Label Improvement: Robust Training by Confidence Based Filtering and Dataset Partitioning

1 code implementation • 7 Feb 2020 • Christian Haase-Schütz, Rainer Stal, Heinz Hertlein, Bernhard Sick

To alleviate this issue, we propose a novel meta training and labelling scheme that is able to use inexpensive unlabelled data by taking advantage of the generalization power of deep neural networks.

Deep Multi-modal Object Detection and Semantic Segmentation for Autonomous Driving: Datasets, Methods, and Challenges

1 code implementation • 21 Feb 2019 • Di Feng, Christian Haase-Schuetz, Lars Rosenbaum, Heinz Hertlein, Claudius Glaeser, Fabian Timm, Werner Wiesbeck, Klaus Dietmayer

This review paper attempts to systematically summarize methodologies and discuss challenges for deep multi-modal object detection and semantic segmentation in autonomous driving.

Robotics