Lidargait: Benchmarking 3d gait recognition with point clouds
Video-based gait recognition has achieved impressive results in constrained scenarios.
However, visual cameras neglect human 3D structure information, which limits the feasibility …
However, visual cameras neglect human 3D structure information, which limits the feasibility …
Icp-flow: Lidar scene flow estimation with icp
Scene flow characterizes the 3D motion between two LiDAR scans captured by an
autonomous vehicle at nearby timesteps. Prevalent methods consider scene flow as point …
autonomous vehicle at nearby timesteps. Prevalent methods consider scene flow as point …
DreamWaQ: Learning robust quadrupedal locomotion with implicit terrain imagination via deep reinforcement learning
Quadrupedal robots resemble the physical ability of legged animals to walk through
unstructured terrains. However, designing a controller for quadrupedal robots poses a …
unstructured terrains. However, designing a controller for quadrupedal robots poses a …
Robust multi-task learning network for complex LiDAR point cloud data preprocessing
L Zhao, Y Hu, X Yang, Z Dou, L Kang - Expert Systems with Applications, 2024 - Elsevier
The utilization of 3D point clouds acquired via Light Detection and Ranging (LiDAR) is
widespread in the fields of autonomous driving, satellite remote sensing, and spatial …
widespread in the fields of autonomous driving, satellite remote sensing, and spatial …
Semoli: What moves together belongs together
We tackle semi-supervised object detection based on motion cues. Recent results suggest
that heuristic-based clustering methods in conjunction with object trackers can be used to …
that heuristic-based clustering methods in conjunction with object trackers can be used to …
Re-evaluating lidar scene flow for autonomous driving
Popular benchmarks for self-supervised LiDAR scene flow (stereoKITTI, and
FlyingThings3D) have unrealistic rates of dynamic motion, unrealistic correspondences, and …
FlyingThings3D) have unrealistic rates of dynamic motion, unrealistic correspondences, and …
Ms3d++: Ensemble of experts for multi-source unsupervised domain adaption in 3d object detection
Deploying 3D detectors in unfamiliar domains has been demonstrated to result in a drastic
drop of up to 70-90% in detection rate due to variations in lidar, geographical region, or …
drop of up to 70-90% in detection rate due to variations in lidar, geographical region, or …
Semi-supervised Class-Agnostic Motion Prediction with Pseudo Label Regeneration and BEVMix
Class-agnostic motion prediction methods aim to comprehend motion within open-world
scenarios, holding significance for autonomous driving systems. However, training a high …
scenarios, holding significance for autonomous driving systems. However, training a high …
RH-Map: Online Map Construction Framework of Dynamic Object Removal Based on 3D Region-wise Hash Map Structure
Mobile robots navigating in outdoor environments frequently encounter the issue of
undesired traces left by dynamic objects and manifested as obstacles on map, impeding …
undesired traces left by dynamic objects and manifested as obstacles on map, impeding …