Search Results for author:
Found 11 papers, 4 papers with code
CMRNext: Camera to LiDAR Matching in the Wild for Localization and Extrinsic Calibration
In this paper, we present CMRNext, a novel approach for camera-LIDAR matching that is independent of sensor-specific parameters, generalizable, and can be used in the wild for monocular localization in LiDAR maps and camera-LiDAR extrinsic calibration.
RaLF: Flow-based Global and Metric Radar Localization in LiDAR Maps
RaLF is composed of radar and LiDAR feature encoders, a place recognition head that generates global descriptors, and a metric localization head that predicts the 3-DoF transformation between the radar scan and the map.
Syn-Mediverse: A Multimodal Synthetic Dataset for Intelligent Scene Understanding of Healthcare Facilities
Safety and efficiency are paramount in healthcare facilities where the lives of patients are at stake.
Unsupervised Domain Adaptation for LiDAR Panoptic Segmentation
Unsupervised Domain Adaptation (UDA) techniques are thus essential to fill this domain gap and retain the performance of models on new sensor setups without the need for additional data labeling.
LCDNet: Deep Loop Closure Detection and Point Cloud Registration for LiDAR SLAM
Loop closure detection is an essential component of Simultaneous Localization and Mapping (SLAM) systems, which reduces the drift accumulated over time.
CMRNet++: Map and Camera Agnostic Monocular Visual Localization in LiDAR Maps
In this paper, we now take it a step further by introducing CMRNet++, which is a significantly more robust model that not only generalizes to new places effectively, but is also independent of the camera parameters.
A Benchmark for Point Clouds Registration Algorithms
In this way, we are able to cover many kinds of environment and many kinds of sensor that can produce point clouds.
Vehicle Ego-Lane Estimation with Sensor Failure Modeling
We present a probabilistic ego-lane estimation algorithm for highway-like scenarios that is designed to increase the accuracy of the ego-lane estimate, which can be obtained relying only on a noisy line detector and tracker.
Global visual localization in LiDAR-maps through shared 2D-3D embedding space
In this work we leverage Deep Neural Network (DNN) approaches to create a shared embedding space between images and LiDAR-maps, allowing for image to 3D-LiDAR place recognition.
CMRNet: Camera to LiDAR-Map Registration
In this paper we present CMRNet, a realtime approach based on a Convolutional Neural Network to localize an RGB image of a scene in a map built from LiDAR data.
A dataset for benchmarking vision-based localization at intersections
Moreover, the dataset is of interest for all those tackling the task of online localization at intersections for road vehicles, e. g., for a quantitative comparison with the proposal in our submitted paper, and it is therefore appropriate to put the dataset description in a separate report.
