33 citations · 133 across the 10 of their papers we have counts for
14 papers · 2 filters
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…
Making a Case for 3D Convolutions for Object Segmentation in Videos
Sabarinath Mahadevan, Ali Athar, Aljoša Ošep +3
The task of object segmentation in videos is usually accomplished by processing appearance and motion information separately using standard 2D convolutional networks, followed by a…
MeTRAbs: Metric-Scale Truncation-Robust Heatmaps for Absolute 3D Human Pose Estimation
István Sárándi, Timm Linder, Kai O. Arras +1
Heatmap representations have formed the basis of human pose estimation systems for many years, and their extension to 3D has been a fruitful line of recent research. This includes…