12 citations · 28 across the 7 of their papers we have counts for
7 papers
CodeSCAN: ScreenCast ANalysis for Video Programming Tutorials
Alexander Naumann, Felix Hertlein, Jacqueline Höllig +2
Programming tutorials in the form of coding screencasts play a crucial role in programming education, serving both novices and experienced developers. However, the video format of…
Heterogeneous Graph-based Trajectory Prediction using Local Map Context and Social Interactions
Daniel Grimm, Maximilian Zipfl, Felix Hertlein +7
Precisely predicting the future trajectories of surrounding traffic participants is a crucial but challenging problem in autonomous driving, due to complex interactions between tra…
TAMPAR: Visual Tampering Detection for Parcel Logistics in Postal Supply Chains
Alexander Naumann, Felix Hertlein, Laura Dörr +1
Due to the steadily rising amount of valuable goods in supply chains, tampering detection for parcels is becoming increasingly important. In this work, we focus on the use-case las…
Parcel3D: Shape Reconstruction from Single RGB Images for Applications in Transportation Logistics
Alexander Naumann, Felix Hertlein, Laura Dörr +1
We focus on enabling damage and tampering detection in logistics and tackle the problem of 3D shape reconstruction of potentially damaged parcels. As input we utilize single RGB im…
Literature Review: Computer Vision Applications in Transportation Logistics and Warehousing
Alexander Naumann, Felix Hertlein, Laura Dörr +2
Computer vision applications in transportation logistics and warehousing have a huge potential for process automation. We present a structured literature review on research in the…
Relation-based Motion Prediction using Traffic Scene Graphs
Maximilian Zipfl, Felix Hertlein, Achim Rettinger +5
Representing relevant information of a traffic scene and understanding its environment is crucial for the success of autonomous driving. Modeling the surrounding of an autonomous c…
Scrape, Cut, Paste and Learn: Automated Dataset Generation Applied to Parcel Logistics
Alexander Naumann, Felix Hertlein, Benchun Zhou +2
State-of-the-art approaches in computer vision heavily rely on sufficiently large training datasets. For real-world applications, obtaining such a dataset is usually a tedious task…