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20202025
most citedDeep Learning for LiDAR Point Clouds in Autonomous Driving: A Review

25 citations · 30 across the 2 of their papers we have counts for

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5 papers · 1 filter

cs.CV2025

SAGOnline: Segment Any Gaussians Online

Wentao Sun, Quanyun Wu, Hanqing Xu +7

3D Gaussian Splatting has emerged as a powerful paradigm for explicit 3D scene representation, yet achieving efficient and consistent 3D segmentation remains challenging. Existing…

cs.CV20215 cited

OpenGF: An Ultra-Large-Scale Ground Filtering Dataset Built Upon Open ALS Point Clouds Around the World

Nannan Qin, Weikai Tan, Lingfei Ma +2

Ground filtering has remained a widely studied but incompletely resolved bottleneck for decades in the automatic generation of high-precision digital elevation model, due to the dr…

cs.CV2020

UAV LiDAR Point Cloud Segmentation of A Stack Interchange with Deep Neural Networks

Weikai Tan, Dedong Zhang, Lingfei Ma +3

Stack interchanges are essential components of transportation systems. Mobile laser scanning (MLS) systems have been widely used in road infrastructure mapping, but accurate mappin…

cs.CV202025 cited

Deep Learning for LiDAR Point Clouds in Autonomous Driving: A Review

Ying Li, Lingfei Ma, Zilong Zhong +4

Recently, the advancement of deep learning in discriminative feature learning from 3D LiDAR data has led to rapid development in the field of autonomous driving. However, automated…

cs.CV2020

Toronto-3D: A Large-scale Mobile LiDAR Dataset for Semantic Segmentation of Urban Roadways

Weikai Tan, Nannan Qin, Lingfei Ma +5

Semantic segmentation of large-scale outdoor point clouds is essential for urban scene understanding in various applications, especially autonomous driving and urban high-definitio…