Semalign: Annotation-free camera-lidar calibration with semantic alignment loss
Multi-sensor solution has been widely adopted in real-world robotics systems (eg, self-
driving vehicles) due to its better robustness. However, its performance is highly dependent …
driving vehicles) due to its better robustness. However, its performance is highly dependent …
Online camera-lidar calibration with sensor semantic information
As a crucial step of sensor data fusion, sensor calibration plays a vital role in many cutting-
edge machine vision applications, such as autonomous vehicles and AR/VR. Existing …
edge machine vision applications, such as autonomous vehicles and AR/VR. Existing …
Semcal: Semantic lidar-camera calibration using neural mutual information estimator
This paper proposes SemCal: an automatic, tar-getless, extrinsic calibration algorithm for a
LiDAR and camera system using semantic information. We leverage a neural information …
LiDAR and camera system using semantic information. We leverage a neural information …
Calibrcnn: Calibrating camera and lidar by recurrent convolutional neural network and geometric constraints
In this paper, we present Calibration Recurrent Convolutional Neural Network (CalibRCNN)
to infer a 6 degrees of freedom (DOF) rigid body transformation between 3D LiDAR and 2D …
to infer a 6 degrees of freedom (DOF) rigid body transformation between 3D LiDAR and 2D …
RGGNet: Tolerance aware LiDAR-camera online calibration with geometric deep learning and generative model
Accurate LiDAR-camera online calibration is critical for modern autonomous vehicles and
robot platforms. Dominant methods heavily rely on hand-crafted features, which are not …
robot platforms. Dominant methods heavily rely on hand-crafted features, which are not …
Unical: a single-branch transformer-based model for camera-to-lidar calibration and validation
M Cocheteux, A Low, M Bruehlmeier - arXiv preprint arXiv:2304.09715, 2023 - arxiv.org
We introduce a novel architecture, UniCal, for Camera-to-LiDAR (C2L) extrinsic calibration
which leverages self-attention mechanisms through a Transformer-based backbone network …
which leverages self-attention mechanisms through a Transformer-based backbone network …
Automatic Target-Less Camera-LiDAR Calibration From Motion and Deep Point Correspondences
Sensor setups of robotic platforms commonly include both camera and LiDAR as they
provide complementary information. However, fusing these two modalities typically requires …
provide complementary information. However, fusing these two modalities typically requires …
Calibformer: A transformer-based automatic lidar-camera calibration network
The fusion of LiDARs and cameras has been increasingly adopted in autonomous driving
for perception tasks. The performance of such fusion-based algorithms largely depends on …
for perception tasks. The performance of such fusion-based algorithms largely depends on …
Causal calibration: iteratively calibrating LiDAR and camera by considering causality and geometry
The external calibration between 3D LiDAR and 2D camera is an extremely important step
towards multimodal fusion for robot perception. However, its accuracy is still unsatisfactory …
towards multimodal fusion for robot perception. However, its accuracy is still unsatisfactory …
ATOP: An attention-to-optimization approach for automatic LiDAR-camera calibration via cross-modal object matching
Y Sun, J Li, Y Wang, X Xu, X Yang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Due to the difference of data modalities, it'sa very challenging task to find the feature
correspondences between 2D and 3D data in LiDAR-Camera calibration. In existing works …
correspondences between 2D and 3D data in LiDAR-Camera calibration. In existing works …