1 citations · 3 across the 13 of their papers we have counts for
13 papers
TAP into the Patch Tokens: Leveraging Vision Foundation Model Features for AI-Generated Image Detection
Ahmed Abdullah, Nikolas Ebert, Oliver Wasenmüller
Recent methods demonstrate that large-scale pretrained models, such as CLIP vision transformers, effectively detect AI-generated images (AIGIs) from unseen generative models when u…
PointTransformerX: Portable and Efficient 3D Point Cloud Processing without Sparse Algorithms
Laurenz Reichardt, Nikolas Ebert, Oliver Wasenmüller
3D point cloud perception remains tightly coupled to custom CUDA operators for spatial operations, limiting portability and efficiency on non-NVIDIA, AMD, and embedded hardware. We…
IonMorphNet: Generalizable Learning of Ion Image Morphologies for Peak Picking in Mass Spectrometry Imaging
Philipp Weigand, Niels Nawrot, Nikolas Ebert +2
Peak picking is a fundamental preprocessing step in Mass Spectrometry Imaging (MSI), where each sample is represented by hundreds to thousands of ion images. Existing approaches re…
SSFT: A Lightweight Spectral-Spatial Fusion Transformer for Generic Hyperspectral Classification
Alexander Musiat, Nikolas Ebert, Oliver Wasenmüller
Hyperspectral imaging enables fine-grained recognition of materials by capturing rich spectral signatures, but learning robust classifiers is challenging due to high dimensionality…
Spatial self-supervised Peak Learning and correlation-based Evaluation of peak picking in Mass Spectrometry Imaging
Philipp Weigand, Nikolas Ebert, Shad A. Mohammed +3
Mass spectrometry imaging (MSI) enables label-free visualization of molecular distributions across tissue samples but generates large and complex datasets that require effective pe…
D-PLS: Decoupled Semantic Segmentation for 4D-Panoptic-LiDAR-Segmentation
Maik Steinhauser, Laurenz Reichardt, Nikolas Ebert +1
This paper introduces a novel approach to 4D Panoptic LiDAR Segmentation that decouples semantic and instance segmentation, leveraging single-scan semantic predictions as prior inf…
Classifier Ensemble for Efficient Uncertainty Calibration of Deep Neural Networks for Image Classification
Michael Schulze, Nikolas Ebert, Laurenz Reichardt +1
This paper investigates novel classifier ensemble techniques for uncertainty calibration applied to various deep neural networks for image classification. We evaluate both accuracy…
Boosting Few-Shot Detection with Large Language Models and Layout-to-Image Synthesis
Ahmed Abdullah, Nikolas Ebert, Oliver Wasenmüller
Recent advancements in diffusion models have enabled a wide range of works exploiting their ability to generate high-volume, high-quality data for use in various downstream tasks.…
GenFormer -- Generated Images are All You Need to Improve Robustness of Transformers on Small Datasets
Sven Oehri, Nikolas Ebert, Ahmed Abdullah +2
Recent studies showcase the competitive accuracy of Vision Transformers (ViTs) in relation to Convolutional Neural Networks (CNNs), along with their remarkable robustness. However,…
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…