15 citations · 18 across the 5 of their papers we have counts for
7 papers · 1 filter
Continual Learning for Class- and Domain-Incremental Semantic Segmentation
Tobias Kalb, Masoud Roschani, Miriam Ruf +1
The field of continual deep learning is an emerging field and a lot of progress has been made. However, concurrently most of the approaches are only tested on the task of image cla…
Deep Sensor Fusion with Pyramid Fusion Networks for 3D Semantic Segmentation
Hannah Schieber, Fabian Duerr, Torsten Schoen +1
Robust environment perception for autonomous vehicles is a tremendous challenge, which makes a diverse sensor set with e.g. camera, lidar and radar crucial. In the process of under…
ReS2tAC -- UAV-Borne Real-Time SGM Stereo Optimized for Embedded ARM and CUDA Devices
Boitumelo Ruf, Jonas Mohrs, Martin Weinmann +2
With the emergence of low-cost robotic systems, such as unmanned aerial vehicle, the importance of embedded high-performance image processing has increased. For a long time, FPGAs…
Do as we do: Multiple Person Video-To-Video Transfer
Mickael Cormier, Houraalsadat Mortazavi Moshkenan, Franz Lörch +2
Our goal is to transfer the motion of real people from a source video to a target video with realistic results. While recent advances significantly improved image-to-image translat…
LiDAR-based Recurrent 3D Semantic Segmentation with Temporal Memory Alignment
Fabian Duerr, Mario Pfaller, Hendrik Weigel +1
Understanding and interpreting a 3d environment is a key challenge for autonomous vehicles. Semantic segmentation of 3d point clouds combines 3d information with semantics and ther…
A Systematic Evaluation of Recent Deep Learning Architectures for Fine-Grained Vehicle Classification
Krassimir Valev, Arne Schumann, Lars Sommer +1
Fine-grained vehicle classification is the task of classifying make, model, and year of a vehicle. This is a very challenging task, because vehicles of different types but similar…