1.1k citations · 1.4k across the 24 of their papers we have counts for
6 papers · 1 filter
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…
(Just) A Spoonful of Refinements Helps the Registration Error Go Down
Sérgio Agostinho, Aljoša Ošep, Alessio Del Bue +1
We tackle data-driven 3D point cloud registration. Given point correspondences, the standard Kabsch algorithm provides an optimal rotation estimate. This allows to train registrati…
EagerMOT: 3D Multi-Object Tracking via Sensor Fusion
Aleksandr Kim, Aljoša Ošep, Laura Leal-Taixé
Multi-object tracking (MOT) enables mobile robots to perform well-informed motion planning and navigation by localizing surrounding objects in 3D space and time. Existing methods r…
Opening up Open-World Tracking
Yang Liu, Idil Esen Zulfikar, Jonathon Luiten +5
Tracking and detecting any object, including ones never-seen-before during model training, is a crucial but elusive capability of autonomous systems. An autonomous agent that is bl…
4D Panoptic LiDAR Segmentation
Mehmet Aygün, Aljoša Ošep, Mark Weber +4
Temporal semantic scene understanding is critical for self-driving cars or robots operating in dynamic environments. In this paper, we propose 4D panoptic LiDAR segmentation to ass…
STEP: Segmenting and Tracking Every Pixel
Mark Weber, Jun Xie, Maxwell Collins +10
The task of assigning semantic classes and track identities to every pixel in a video is called video panoptic segmentation. Our work is the first that targets this task in a real-…