4 papers
UAV-MM3D: A Large-Scale Synthetic Benchmark for 3D Perception of Unmanned Aerial Vehicles with Multi-Modal Data
Longkun Zou, Jiale Wang, Rongqin Liang +3
Accurate perception of UAVs in complex low-altitude environments is critical for airspace security and related intelligent systems. Developing reliable solutions requires large-sca…
LAA3D: A Benchmark of Detecting and Tracking Low-Altitude Aircraft in 3D Space
Hai Wu, Shuai Tang, Jiale Wang +5
Perception of Low-Altitude Aircraft (LAA) in 3D space enables precise 3D object localization and behavior understanding. However, datasets tailored for 3D LAA perception remain sca…
Topology-Aware Modeling for Unsupervised Simulation-to-Reality Point Cloud Recognition
Longkun Zou, Kangjun Liu, Ke Chen +3
Learning semantic representations from point sets of 3D object shapes is often challenged by significant geometric variations, primarily due to differences in data acquisition meth…
Bridging Domain Gap of Point Cloud Representations via Self-Supervised Geometric Augmentation
Li Yu, Hongchao Zhong, Longkun Zou +2
Recent progress of semantic point clouds analysis is largely driven by synthetic data (e.g., the ModelNet and the ShapeNet), which are typically complete, well-aligned and noisy fr…