33 citations · 116 across the 8 of their papers we have counts for
35 papers · 1 filter
Person-MinkUNet: 3D Person Detection with LiDAR Point Cloud
Dan Jia, Bastian Leibe
In this preliminary work we attempt to apply submanifold sparse convolution to the task of 3D person detection. In particular, we present Person-MinkUNet, a single-stage 3D person…
From Points to Multi-Object 3D Reconstruction
Francis Engelmann, Konstantinos Rematas, Bastian Leibe +1
We propose a method to detect and reconstruct multiple 3D objects from a single RGB image. The key idea is to optimize for detection, alignment and shape jointly over all objects i…
Self-Supervised Person Detection in 2D Range Data using a Calibrated Camera
Dan Jia, Mats Steinweg, Alexander Hermans +1
Deep learning is the essential building block of state-of-the-art person detectors in 2D range data. However, only a few annotated datasets are available for training and testing t…
Reducing the Annotation Effort for Video Object Segmentation Datasets
Paul Voigtlaender, Lishu Luo, Chun Yuan +2
For further progress in video object segmentation (VOS), larger, more diverse, and more challenging datasets will be necessary. However, densely labeling every frame with pixel mas…
HOTA: A Higher Order Metric for Evaluating Multi-Object Tracking
Jonathon Luiten, Aljosa Osep, Patrick Dendorfer +4
Multi-Object Tracking (MOT) has been notoriously difficult to evaluate. Previous metrics overemphasize the importance of either detection or association. To address this, we presen…
SAMP: Shape and Motion Priors for 4D Vehicle Reconstruction
Francis Engelmann, Jörg Stückler, Bastian Leibe
Inferring the pose and shape of vehicles in 3D from a movable platform still remains a challenging task due to the projective sensing principle of cameras, difficult surface proper…