229 citations · 1k across the 84 of their papers we have counts for
8 papers · 1 filter
PADLoC: LiDAR-Based Deep Loop Closure Detection and Registration Using Panoptic Attention
José Arce, Niclas Vödisch, Daniele Cattaneo +2
A key component of graph-based SLAM systems is the ability to detect loop closures in a trajectory to reduce the drift accumulated over time from the odometry. Most LiDAR-based met…
Perceiving the Invisible: Proposal-Free Amodal Panoptic Segmentation
Rohit Mohan, Abhinav Valada
Amodal panoptic segmentation aims to connect the perception of the world to its cognitive understanding. It entails simultaneously predicting the semantic labels of visible scene r…
On Hyperbolic Embeddings in 2D Object Detection
Christopher Lang, Alexander Braun, Abhinav Valada
Object detection, for the most part, has been formulated in the euclidean space, where euclidean or spherical geodesic distances measure the similarity of an image region to an obj…
3D Multi-Object Tracking Using Graph Neural Networks with Cross-Edge Modality Attention
Martin Buchner, Abhinav Valada
Online 3D multi-object tracking (MOT) has witnessed significant research interest in recent years, largely driven by demand from the autonomous systems community. However, 3D offli…
Continual SLAM: Beyond Lifelong Simultaneous Localization and Mapping Through Continual Learning
Niclas Vödisch, Daniele Cattaneo, Wolfram Burgard +1
Robots operating in the open world encounter various different environments that can substantially differ from each other. This domain gap also poses a challenge for Simultaneous L…
OpenDR: An Open Toolkit for Enabling High Performance, Low Footprint Deep Learning for Robotics
N. Passalis, S. Pedrazzi, R. Babuska +15
Existing Deep Learning (DL) frameworks typically do not provide ready-to-use solutions for robotics, where very specific learning, reasoning, and embodiment problems exist. Their r…
Amodal Panoptic Segmentation
Rohit Mohan, Abhinav Valada
Humans have the remarkable ability to perceive objects as a whole, even when parts of them are occluded. This ability of amodal perception forms the basis of our perceptual and cog…
Neural Architecture Search for Dense Prediction Tasks in Computer Vision
Thomas Elsken, Arber Zela, Jan Hendrik Metzen +4
The success of deep learning in recent years has lead to a rising demand for neural network architecture engineering. As a consequence, neural architecture search (NAS), which aims…