[HTML][HTML] An efficient image-guided-based 3D point cloud moving object segmentation with transformer-attention in autonomous driving
Q Li, Y Zhuang - International Journal of Applied Earth Observation and …, 2023 - Elsevier
For intelligent transportation systems, moving object segmentation (MOS) provides valuable
information for robots and intelligent vehicles, such as collision avoidance, path planning …
information for robots and intelligent vehicles, such as collision avoidance, path planning …
Moving object segmentation in 3D LiDAR data: A learning-based approach exploiting sequential data
The ability to detect and segment moving objects in a scene is essential for building
consistent maps, making future state predictions, avoiding collisions, and planning. In this …
consistent maps, making future state predictions, avoiding collisions, and planning. In this …
ERASOR: Egocentric ratio of pseudo occupancy-based dynamic object removal for static 3D point cloud map building
Scan data of urban environments often include representations of dynamic objects, such as
vehicles, pedestrians, and so forth. However, when it comes to constructing a 3D point cloud …
vehicles, pedestrians, and so forth. However, when it comes to constructing a 3D point cloud …
Dynamic 3d scene analysis by point cloud accumulation
Multi-beam LiDAR sensors, as used on autonomous vehicles and mobile robots, acquire
sequences of 3D range scans (“frames”). Each frame covers the scene sparsely, due to …
sequences of 3D range scans (“frames”). Each frame covers the scene sparsely, due to …
Automatic labeling to generate training data for online LiDAR-based moving object segmentation
Understanding the scene is key for autonomously navigating vehicles, and the ability to
segment the surroundings online into moving and non-moving objects is a central ingredient …
segment the surroundings online into moving and non-moving objects is a central ingredient …
Receding moving object segmentation in 3d lidar data using sparse 4d convolutions
A key challenge for autonomous vehicles is to navigate in unseen dynamic environments.
Separating moving objects from static ones is essential for navigation, pose estimation, and …
Separating moving objects from static ones is essential for navigation, pose estimation, and …
3D semantic scene completion: A survey
Semantic scene completion (SSC) aims to jointly estimate the complete geometry and
semantics of a scene, assuming partial sparse input. In the last years following the …
semantics of a scene, assuming partial sparse input. In the last years following the …
Efficient spatial-temporal information fusion for lidar-based 3d moving object segmentation
Accurate moving object segmentation is an es-sential task for autonomous driving. It can
provide effective information for many downstream tasks, such as collision avoidance, path …
provide effective information for many downstream tasks, such as collision avoidance, path …
Building volumetric beliefs for dynamic environments exploiting map-based moving object segmentation
Mobile robots that navigate in unknown environments need to be constantly aware of the
dynamic objects in their surroundings for map**, localization, and planning. It is key to …
dynamic objects in their surroundings for map**, localization, and planning. It is key to …
Rf-lio: Removal-first tightly-coupled lidar inertial odometry in high dynamic environments
C Qian, Z ** (SLAM) is considered to be an essential capability
for intelligent vehicles and mobile robots. However, most of the current lidar SLAM …
for intelligent vehicles and mobile robots. However, most of the current lidar SLAM …