Search Results for author: Aleksandr Kim

Found 2 papers, 1 papers with code

PolarMOT: How Far Can Geometric Relations Take Us in 3D Multi-Object Tracking?

no code implementations • 3 Aug 2022 • Aleksandr Kim, Guillem Brasó, Aljoša Ošep, Laura Leal-Taixé

This allows our graph neural network to learn to effectively encode temporal and spatial interactions and fully leverage contextual and motion cues to obtain final scene interpretation by posing data association as edge classification.

3D Multi-Object Tracking Edge Classification

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EagerMOT: 3D Multi-Object Tracking via Sensor Fusion

3 code implementations • 29 Apr 2021 • 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.

Ranked #1 on 3D Multi-Object Tracking on KITTI

3D Multi-Object Tracking Motion Planning +4

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