SPAMming Labels: Efficient Annotations for the Trackers of Tomorrow

no code implementations • 17 Apr 2024 • Orcun Cetintas, Tim Meinhardt, Guillem Brasó, Laura Leal-Taixé

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-scale datasets.

Unifying Short and Long-Term Tracking with Graph Hierarchies

1 code implementation • CVPR 2023 • 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 are occluded and then reappear in the scene.

Multiple Object Tracking

Multi-Object Tracking and Segmentation via Neural Message Passing

1 code implementation • 15 Jul 2022 • Guillem Braso, Orcun Cetintas, Laura Leal-Taixe

We achieve state-of-the-art results for both tracking and segmentation in several publicly available datasets.

Multi-Object Tracking Multi-Object Tracking and Segmentation +2

MOTSynth: How Can Synthetic Data Help Pedestrian Detection and Tracking?

1 code implementation • ICCV 2021 • Matteo Fabbri, Guillem Braso, Gianluca Maugeri, Orcun Cetintas, Riccardo Gasparini, Aljosa Osep, Simone Calderara, Laura Leal-Taixe, Rita Cucchiara

Deep learning-based methods for video pedestrian detection and tracking require large volumes of training data to achieve good performance.

object-detection Object Detection +1