26 citations · 75 across the 21 of their papers we have counts for
28 papers
Generative Texture Diversification of 3D Pedestrians for Robust Autonomous Driving Perception
Arka Bhowmick, Enes Ozeren, Ahmed Abdullah +1
In recent years, autonomous driving has significantly in creased the demand for high-quality data to train 2D and 3D perception models for safety-critical scenarios. Real world dat…
RadarPillars: Efficient Object Detection from 4D Radar Point Clouds
Alexander Musiat, Laurenz Reichardt, Michael Schulze +1
Automotive radar systems have evolved to provide not only range, azimuth and Doppler velocity, but also elevation data. This additional dimension allows for the representation of 4…
360 from a Single Camera: A Few-Shot Approach for LiDAR Segmentation
Laurenz Reichardt, Nikolas Ebert, Oliver Wasenmüller
Deep learning applications on LiDAR data suffer from a strong domain gap when applied to different sensors or tasks. In order for these methods to obtain similar accuracy on differ…
Transformer-based Detection of Microorganisms on High-Resolution Petri Dish Images
Nikolas Ebert, Didier Stricker, Oliver Wasenmüller
Many medical or pharmaceutical processes have strict guidelines regarding continuous hygiene monitoring. This often involves the labor-intensive task of manually counting microorga…
Light-Weight Vision Transformer with Parallel Local and Global Self-Attention
Nikolas Ebert, Laurenz Reichardt, Didier Stricker +1
While transformer architectures have dominated computer vision in recent years, these models cannot easily be deployed on hardware with limited resources for autonomous driving tas…
Multitask Network for Joint Object Detection, Semantic Segmentation and Human Pose Estimation in Vehicle Occupancy Monitoring
Nikolas Ebert, Patrick Mangat, Oliver Wasenmüller
In order to ensure safe autonomous driving, precise information about the conditions in and around the vehicle must be available. Accordingly, the monitoring of occupants and objec…
Detection of Driver Drowsiness by Calculating the Speed of Eye Blinking
Muhammad Fawwaz Yusri, Patrick Mangat, Oliver Wasenmüller
Many road accidents are caused by drowsiness of the driver. While there are methods to detect closed eyes, it is a non-trivial task to detect the gradual process of a driver becomi…
PDC: Piecewise Depth Completion utilizing Superpixels
Dennis Teutscher, Patrick Mangat, Oliver Wasenmüller
Depth completion from sparse LiDAR and high-resolution RGB data is one of the foundations for autonomous driving techniques. Current approaches often rely on CNN-based methods with…
DVMN: Dense Validity Mask Network for Depth Completion
Laurenz Reichardt, Patrick Mangat, Oliver Wasenmüller
LiDAR depth maps provide environmental guidance in a variety of applications. However, such depth maps are typically sparse and insufficient for complex tasks such as autonomous na…
Autoencoder Based Inter-Vehicle Generalization for In-Cabin Occupant Classification
Steve Dias Da Cruz, Bertram Taetz, Oliver Wasenmüller +2
Common domain shift problem formulations consider the integration of multiple source domains, or the target domain during training. Regarding the generalization of machine learning…
SALT: A Semi-automatic Labeling Tool for RGB-D Video Sequences
Dennis Stumpf, Stephan Krauß, Gerd Reis +2
Large labeled data sets are one of the essential basics of modern deep learning techniques. Therefore, there is an increasing need for tools that allow to label large amounts of da…
HPERL: 3D Human Pose Estimation from RGB and LiDAR
Michael Fürst, Shriya T. P. Gupta, René Schuster +2
In-the-wild human pose estimation has a huge potential for various fields, ranging from animation and action recognition to intention recognition and prediction for autonomous driv…
DeepLiDARFlow: A Deep Learning Architecture For Scene Flow Estimation Using Monocular Camera and Sparse LiDAR
Rishav, Ramy Battrawy, René Schuster +2
Scene flow is the dense 3D reconstruction of motion and geometry of a scene. Most state-of-the-art methods use a pair of stereo images as input for full scene reconstruction. These…
SSGP: Sparse Spatial Guided Propagation for Robust and Generic Interpolation
René Schuster, Oliver Wasenmüller, Christian Unger +1
Interpolation of sparse pixel information towards a dense target resolution finds its application across multiple disciplines in computer vision. State-of-the-art interpolation of…
ResFPN: Residual Skip Connections in Multi-Resolution Feature Pyramid Networks for Accurate Dense Pixel Matching
Rishav, René Schuster, Ramy Battrawy +2
Dense pixel matching is required for many computer vision algorithms such as disparity, optical flow or scene flow estimation. Feature Pyramid Networks (FPN) have proven to be a su…
LRPD: Long Range 3D Pedestrian Detection Leveraging Specific Strengths of LiDAR and RGB
Michael Fürst, Oliver Wasenmüller, Didier Stricker
While short range 3D pedestrian detection is sufficient for emergency breaking, long range detections are required for smooth breaking and gaining trust in autonomous vehicles. The…
DFKI Cabin Simulator: A Test Platform for Visual In-Cabin Monitoring Functions
Hartmut Feld, Bruno Mirbach, Jigyasa Katrolia +3
We present a test platform for visual in-cabin scene analysis and occupant monitoring functions. The test platform is based on a driving simulator developed at the DFKI, consisting…
SVIRO: Synthetic Vehicle Interior Rear Seat Occupancy Dataset and Benchmark
Steve Dias Da Cruz, Oliver Wasenmüller, Hans-Peter Beise +2
We release SVIRO, a synthetic dataset for sceneries in the passenger compartment of ten different vehicles, in order to analyze machine learning-based approaches for their generali…
LiDAR-Flow: Dense Scene Flow Estimation from Sparse LiDAR and Stereo Images
Ramy Battrawy, René Schuster, Oliver Wasenmüller +2
We propose a new approach called LiDAR-Flow to robustly estimate a dense scene flow by fusing a sparse LiDAR with stereo images. We take the advantage of the high accuracy of LiDAR…
A Compact Light Field Camera for Real-Time Depth Estimation
Yuriy Anisimov, Oliver Wasenmüller, Didier Stricker
Depth cameras are utilized in many applications. Recently light field approaches are increasingly being used for depth computation. While these approaches demonstrate the technical…
DeLiO: Decoupled LiDAR Odometry
Queens Maria Thomas, Oliver Wasenmüller, Didier Stricker
Most LiDAR odometry algorithms estimate the transformation between two consecutive frames by estimating the rotation and translation in an intervening fashion. In this paper, we pr…
An Empirical Evaluation Study on the Training of SDC Features for Dense Pixel Matching
René Schuster, Oliver Wasenmüller, Christian Unger +1
Training a deep neural network is a non-trivial task. Not only the tuning of hyperparameters, but also the gathering and selection of training data, the design of the loss function…
PWOC-3D: Deep Occlusion-Aware End-to-End Scene Flow Estimation
Rohan Saxena, René Schuster, Oliver Wasenmüller +1
In the last few years, convolutional neural networks (CNNs) have demonstrated increasing success at learning many computer vision tasks including dense estimation problems such as…
SceneFlowFields++: Multi-frame Matching, Visibility Prediction, and Robust Interpolation for Scene Flow Estimation
René Schuster, Oliver Wasenmüller, Christian Unger +2
State-of-the-art scene flow algorithms pursue the conflicting targets of accuracy, run time, and robustness. With the successful concept of pixel-wise matching and sparse-to-dense…