Occlusion is commonplace in realistic human-robot shared environments, yet its effects are not considered in standard 3D human pose estimation benchm…
With the rise of end-to-end learning through deep learning, person detectors and re-identification (ReID) models have recently become very strong. Mu…
We present a novel end-to-end single-shot method that segments countable object instances (things) as well as background regions (stuff) into a non-o…
Recent progress in Reinforcement Learning (RL), fueled by its combination, with Deep Learning has enabled impressive results in learning to interact …
In this paper, we present a deep learning architecture which addresses the problem of 3D semantic segmentation of unstructured point clouds. Compared…
Object tracking and reconstruction are often performed together, with tracking used as input for 3D reconstrution. However, the obtained 3D reconstru…
Deep learning approaches have made tremendous progress in the field of semantic segmentation over the past few years. However, most current approache…
Deep learning requires large amounts of training data to be effective. For the task of object segmentation, manually labeling data is very expensive,…
In this paper we present our winning entry at the 2018 ECCV PoseTrack Challenge on 3D human pose estimation. Using a fully-convolutional backbone arc…
Tracking in urban street scenes plays a central role in autonomous systems such as self-driving cars. Most of the current vision-based tracking metho…
We propose to leverage a generic object tracker in order to perform object mining in large-scale unlabeled videos, captured in a realistic automotive…
We tackle the task of semi-supervised video object segmentation, i.e. segmenting the pixels belonging to an object in the video using the ground trut…
Micro aerial vehicles (MAVs) are strongly limited in their payload and power capacity. In order to implement autonomous navigation, algorithms are th…
We explore object discovery and detector adaptation based on unlabeled video sequences captured from a mobile platform. We propose a fully automatic …
In the past decade many robots were deployed in the wild, and people detection and tracking is an important component of such deployments. On top of …
We address semi-supervised video object segmentation, the task of automatically generating accurate and consistent pixel masks for objects in a video…
The most common paradigm for vision-based multi-object tracking is tracking-by-detection, due to the availability of reliable detectors for several i…
Many high-level video understanding methods require input in the form of object proposals. Currently, such proposals are predominantly generated with…
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