133 citations · 259 across the 13 of their papers we have counts for
15 papers
Why Domain Matters: A Preliminary Study of Domain Effects in Underwater Object Detection
Melanie Wille, Dimity Miller, Tobias Fischer +1
Domain shift, where deviations between training and deployment data distributions degrade model performance, is a key challenge in underwater environments. Existing benchmarks test…
R3D3: Dense 3D Reconstruction of Dynamic Scenes from Multiple Cameras
Aron Schmied, Tobias Fischer, Martin Danelljan +2
Dense 3D reconstruction and ego-motion estimation are key challenges in autonomous driving and robotics. Compared to the complex, multi-modal systems deployed today, multi-camera s…
OVTrack: Open-Vocabulary Multiple Object Tracking
Siyuan Li, Tobias Fischer, Lei Ke +3
The ability to recognize, localize and track dynamic objects in a scene is fundamental to many real-world applications, such as self-driving and robotic systems. Yet, traditional m…
Visual Place Recognition: A Tutorial
Stefan Schubert, Peer Neubert, Sourav Garg +2
Localization is an essential capability for mobile robots. A rapidly growing field of research in this area is Visual Place Recognition (VPR), which is the ability to recognize pre…
Image Labels Are All You Need for Coarse Seagrass Segmentation
Scarlett Raine, Ross Marchant, Brano Kusy +2
Seagrass meadows serve as critical carbon sinks, but estimating the amount of carbon they store requires knowledge of the seagrass species present. Underwater and surface vehicles…
CC-3DT: Panoramic 3D Object Tracking via Cross-Camera Fusion
Tobias Fischer, Yung-Hsu Yang, Suryansh Kumar +2
To track the 3D locations and trajectories of the other traffic participants at any given time, modern autonomous vehicles are equipped with multiple cameras that cover the vehicle…
Boosting Performance of a Baseline Visual Place Recognition Technique by Predicting the Maximally Complementary Technique
Connor Malone, Stephen Hausler, Tobias Fischer +1
One recent promising approach to the Visual Place Recognition (VPR) problem has been to fuse the place recognition estimates of multiple complementary VPR techniques using methods…
QDTrack: Quasi-Dense Similarity Learning for Appearance-Only Multiple Object Tracking
Tobias Fischer, Thomas E. Huang, Jiangmiao Pang +4
Similarity learning has been recognized as a crucial step for object tracking. However, existing multiple object tracking methods only use sparse ground truth matching as the train…
SAFE: Sensitivity-Aware Features for Out-of-Distribution Object Detection
Samuel Wilson, Tobias Fischer, Feras Dayoub +2
We address the problem of out-of-distribution (OOD) detection for the task of object detection. We show that residual convolutional layers with batch normalisation produce Sensitiv…
How Many Events do You Need? Event-based Visual Place Recognition Using Sparse But Varying Pixels
Tobias Fischer, Michael Milford
Event cameras continue to attract interest due to desirable characteristics such as high dynamic range, low latency, virtually no motion blur, and high energy efficiency. One of th…
Point Label Aware Superpixels for Multi-species Segmentation of Underwater Imagery
Scarlett Raine, Ross Marchant, Brano Kusy +2
Monitoring coral reefs using underwater vehicles increases the range of marine surveys and availability of historical ecological data by collecting significant quantities of images…
Unsupervised Complementary-aware Multi-process Fusion for Visual Place Recognition
Stephen Hausler, Tobias Fischer, Michael Milford
A recent approach to the Visual Place Recognition (VPR) problem has been to fuse the place recognition estimates of multiple complementary VPR techniques simultaneously. However, s…
Hyperdimensional Feature Fusion for Out-Of-Distribution Detection
Samuel Wilson, Tobias Fischer, Niko Sünderhauf +1
We introduce powerful ideas from Hyperdimensional Computing into the challenging field of Out-of-Distribution (OOD) detection. In contrast to most existing work that performs OOD d…
Monocular Quasi-Dense 3D Object Tracking
Hou-Ning Hu, Yung-Hsu Yang, Tobias Fischer +3
A reliable and accurate 3D tracking framework is essential for predicting future locations of surrounding objects and planning the observer's actions in numerous applications such…
Track to Reconstruct and Reconstruct to Track
Jonathon Luiten, Tobias Fischer, Bastian Leibe
Object tracking and 3D reconstruction are often performed together, with tracking used as input for reconstruction. However, the obtained reconstructions also provide useful inform…