986 citations · 1k across the 4 of their papers we have counts for
5 papers
Detecting Unexpected Obstacles for Self-Driving Cars: Fusing Deep Learning and Geometric Modeling
Sebastian Ramos, Stefan Gehrig, Peter Pinggera +2
The detection of small road hazards, such as lost cargo, is a vital capability for self-driving cars. We tackle this challenging and rarely addressed problem with a vision system t…
Lost and Found: Detecting Small Road Hazards for Self-Driving Vehicles
Peter Pinggera, Sebastian Ramos, Stefan Gehrig +3
Detecting small obstacles on the road ahead is a critical part of the driving task which has to be mastered by fully autonomous cars. In this paper, we present a method based on st…
The Cityscapes Dataset for Semantic Urban Scene Understanding
Marius Cordts, Mohamed Omran, Sebastian Ramos +6
Visual understanding of complex urban street scenes is an enabling factor for a wide range of applications. Object detection has benefited enormously from large-scale datasets, esp…
Hierarchical Adaptive Structural SVM for Domain Adaptation
Jiaolong Xu, Sebastian Ramos, David Vazquez +1
A key topic in classification is the accuracy loss produced when the data distribution in the training (source) domain differs from that in the testing (target) domain. This is bei…
Spatiotemporal Stacked Sequential Learning for Pedestrian Detection
Alejandro González, Sebastian Ramos, David Vázquez +2
Pedestrian classifiers decide which image windows contain a pedestrian. In practice, such classifiers provide a relatively high response at neighbor windows overlapping a pedestria…