7 citations · 13 across the 6 of their papers we have counts for
7 papers
Beyond the Image Plane: World-Grounded Queries for Multi-Object Tracking
Orcun Cetintas, Guillem Brasó, Tim Meinhardt +1
Monocular videos record 3D scenes as sequences of 2D image-plane projections, obscuring depth and spatial relationships. Multi-object trackers localize and associate objects primar…
NOOUGAT: Towards Unified Online and Offline Multi-Object Tracking
Benjamin Missaoui, Orcun Cetintas, Guillem Brasó +2
The long-standing division between \textit{online} and \textit{offline} Multi-Object Tracking (MOT) has led to fragmented solutions that fail to address the flexible temporal requi…
MCBLT: Multi-Camera Multi-Object 3D Tracking in Long Videos
Yizhou Wang, Tim Meinhardt, Orcun Cetintas +6
Object perception from multi-view cameras is crucial for intelligent systems, particularly in indoor environments, e.g., warehouses, retail stores, and hospitals. Most traditional…
SPAMming Labels: Efficient Annotations for the Trackers of Tomorrow
Orcun Cetintas, Tim Meinhardt, Guillem Brasó +1
Increasing the annotation efficiency of trajectory annotations from videos has the potential to enable the next generation of data-hungry tracking algorithms to thrive on large-sca…
Unifying Short and Long-Term Tracking with Graph Hierarchies
Orcun Cetintas, Guillem Brasó, Laura Leal-Taixé
Tracking objects over long videos effectively means solving a spectrum of problems, from short-term association for un-occluded objects to long-term association for objects that ar…
Multi-Object Tracking and Segmentation via Neural Message Passing
Guillem Braso, Orcun Cetintas, Laura Leal-Taixe
Graphs offer a natural way to formulate Multiple Object Tracking (MOT) and Multiple Object Tracking and Segmentation (MOTS) within the tracking-by-detection paradigm. However, they…
MOTSynth: How Can Synthetic Data Help Pedestrian Detection and Tracking?
Matteo Fabbri, Guillem Braso, Gianluca Maugeri +6
Deep learning-based methods for video pedestrian detection and tracking require large volumes of training data to achieve good performance. However, data acquisition in crowded pub…