Occ3d: A large-scale 3d occupancy prediction benchmark for autonomous driving
Robotic perception requires the modeling of both 3D geometry and semantics. Existing
methods typically focus on estimating 3D bounding boxes, neglecting finer geometric details …
methods typically focus on estimating 3D bounding boxes, neglecting finer geometric details …
Kiss-icp: In defense of point-to-point icp–simple, accurate, and robust registration if done the right way
Robust and accurate pose estimation of a robotic platform, so-called sensor-based
odometry, is an essential part of many robotic applications. While many sensor odometry …
odometry, is an essential part of many robotic applications. While many sensor odometry …
Neural kernel surface reconstruction
We present a novel method for reconstructing a 3D implicit surface from a large-scale,
sparse, and noisy point cloud. Our approach builds upon the recently introduced Neural …
sparse, and noisy point cloud. Our approach builds upon the recently introduced Neural …
Streetsurf: Extending multi-view implicit surface reconstruction to street views
We present a novel multi-view implicit surface reconstruction technique, termed StreetSurf,
that is readily applicable to street view images in widely-used autonomous driving datasets …
that is readily applicable to street view images in widely-used autonomous driving datasets …
Nerf-loam: Neural implicit representation for large-scale incremental lidar odometry and mapping
Simultaneously odometry and mapping using LiDAR data is an important task for mobile
systems to achieve full autonomy in large-scale environments. However, most existing …
systems to achieve full autonomy in large-scale environments. However, most existing …
Sloper4d: A scene-aware dataset for global 4d human pose estimation in urban environments
We present SLOPER4D, a novel scene-aware dataset collected in large urban
environments to facilitate the research of global human pose estimation (GHPE) with human …
environments to facilitate the research of global human pose estimation (GHPE) with human …
Shine-mapping: Large-scale 3d mapping using sparse hierarchical implicit neural representations
Accurate mapping of large-scale environments is an essential building block of most outdoor
autonomous systems. Challenges of traditional mapping methods include the balance …
autonomous systems. Challenges of traditional mapping methods include the balance …
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 mapping, localization, and planning. It is key to …
dynamic objects in their surroundings for mapping, localization, and planning. It is key to …
Locndf: Neural distance field mapping for robot localization
Mapping an environment is essential for several robotic tasks, particularly for localization. In
this letter, we address the problem of mapping the environment using LiDAR point clouds …
this letter, we address the problem of mapping the environment using LiDAR point clouds …
Fast-livo2: Fast, direct lidar-inertial-visual odometry
This paper presents FAST-LIVO2, a fast and direct LiDAR-inertial-visual odometry
framework designed for accurate and robust state estimation in SLAM tasks, enabling real …
framework designed for accurate and robust state estimation in SLAM tasks, enabling real …