7 citations · 15 across the 5 of their papers we have counts for
7 papers · 1 filter
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…
PolarMOT: How Far Can Geometric Relations Take Us in 3D Multi-Object Tracking?
Aleksandr Kim, Guillem Brasó, Aljoša Ošep +1
Most (3D) multi-object tracking methods rely on appearance-based cues for data association. By contrast, we investigate how far we can get by only encoding geometric relationships…
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…
Simple Cues Lead to a Strong Multi-Object Tracker
Jenny Seidenschwarz, Guillem Brasó, Victor Castro Serrano +2
For a long time, the most common paradigm in Multi-Object Tracking was tracking-by-detection (TbD), where objects are first detected and then associated over video frames. For asso…
The Center of Attention: Center-Keypoint Grouping via Attention for Multi-Person Pose Estimation
Guillem Brasó, Nikita Kister, Laura Leal-Taixé
We introduce CenterGroup, an attention-based framework to estimate human poses from a set of identity-agnostic keypoints and person center predictions in an image. Our approach use…
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…