Text2Pos: Text-to-Point-Cloud Cross-Modal Localization

no code implementations • CVPR 2022 • Manuel Kolmet, Qunjie Zhou, Aljosa Osep, Laura Leal-Taixe

Natural language-based communication with mobile devices and home appliances is becoming increasingly popular and has the potential to become natural for communicating with mobile robots in the future.

Is Geometry Enough for Matching in Visual Localization?

1 code implementation • 24 Mar 2022 • Qunjie Zhou, Sérgio Agostinho, Aljosa Osep, Laura Leal-Taixé

In this paper, we propose to go beyond the well-established approach to vision-based localization that relies on visual descriptor matching between a query image and a 3D point cloud.

Visual Localization

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

HOTA: A Higher Order Metric for Evaluating Multi-Object Tracking

5 code implementations • 16 Sep 2020 • Jonathon Luiten, Aljosa Osep, Patrick Dendorfer, Philip Torr, Andreas Geiger, Laura Leal-Taixe, Bastian Leibe

Multi-Object Tracking (MOT) has been notoriously difficult to evaluate.

Multi-Object Tracking

AlignNet-3D: Fast Point Cloud Registration of Partially Observed Objects

1 code implementation • 10 Oct 2019 • Johannes Groß, Aljosa Osep, Bastian Leibe

In this work, we focus on precise 3D track state estimation and propose a learning-based approach for object-centric relative motion estimation of partially observed objects.

3D Pose Estimation Motion Estimation +2

How To Train Your Deep Multi-Object Tracker

2 code implementations • CVPR 2020 • Yihong Xu, Aljosa Osep, Yutong Ban, Radu Horaud, Laura Leal-Taixe, Xavier Alameda-Pineda

In this paper, we bridge this gap by proposing a differentiable proxy of MOTA and MOTP, which we combine in a loss function suitable for end-to-end training of deep multi-object trackers.

Multi-Object Tracking Multiple Object Tracking +1

Large-Scale Object Mining for Object Discovery from Unlabeled Video

no code implementations • 28 Feb 2019 • Aljosa Osep, Paul Voigtlaender, Jonathon Luiten, Stefan Breuers, Bastian Leibe

This paper addresses the problem of object discovery from unlabeled driving videos captured in a realistic automotive setting.

Clustering Object +1

MOTS: Multi-Object Tracking and Segmentation

no code implementations • CVPR 2019 • Paul Voigtlaender, Michael Krause, Aljosa Osep, Jonathon Luiten, Berin Balachandar Gnana Sekar, Andreas Geiger, Bastian Leibe

This paper extends the popular task of multi-object tracking to multi-object tracking and segmentation (MOTS).

Multi-Object Tracking Multi-Object Tracking and Segmentation +3

4D Generic Video Object Proposals

1 code implementation • 26 Jan 2019 • Aljosa Osep, Paul Voigtlaender, Mark Weber, Jonathon Luiten, Bastian Leibe

Many high-level video understanding methods require input in the form of object proposals.

Instance Segmentation Object +2

Towards Large-Scale Video Video Object Mining

no code implementations • 19 Sep 2018 • Aljosa Osep, Paul Voigtlaender, Jonathon Luiten, Stefan Breuers, Bastian Leibe

We propose to leverage a generic object tracker in order to perform object mining in large-scale unlabeled videos, captured in a realistic automotive setting.

Object

Combined Image- and World-Space Tracking in Traffic Scenes

no code implementations • 19 Sep 2018 • Aljosa Osep, Wolfgang Mehner, Markus Mathias, Bastian Leibe

Most of the current vision-based tracking methods perform tracking in the image domain.

Multiple Object Tracking Self-Driving Cars