Search Results for author: Congcong Wen

Found 5 papers, 2 papers with code

Fooling LiDAR Perception via Adversarial Trajectory Perturbation

1 code implementation ICCV 2021 Yiming Li, Congcong Wen, Felix Juefei-Xu, Chen Feng

LiDAR point clouds collected from a moving vehicle are functions of its trajectories, because the sensor motion needs to be compensated to avoid distortions.

3D Object Detection Autonomous Vehicles +2

AETree: Areal Spatial Data Generation

no code implementations1 Jan 2021 Congcong Wen, Wenyu Han, Hang Zhao, Chen Feng

Areal spatial data represent not only geographical locations but also sizes and shapes of physical objects such as buildings in a city.

Airborne LiDAR Point Cloud Classification with Graph Attention Convolution Neural Network

no code implementations20 Apr 2020 Congcong Wen, Xiang Li, Xiaojing Yao, Ling Peng, Tianhe Chi

To achieve point cloud classification, previous studies proposed point cloud deep learning models that can directly process raw point clouds based on PointNet-like architectures.

General Classification Graph Attention +2

Density-Aware Convolutional Networks with Context Encoding for Airborne LiDAR Point Cloud Classification

no code implementations14 Oct 2019 Xiang Li, Mingyang Wang, Congcong Wen, Lingjing Wang, Nan Zhou, Yi Fang

Based on this convolution module, we further developed a multi-scale fully convolutional neural network with downsampling and upsampling blocks to enable hierarchical point feature learning.

3D Point Cloud Classification General Classification +1

Directionally Constrained Fully Convolutional Neural Network For Airborne Lidar Point Cloud Classification

1 code implementation19 Aug 2019 Congcong Wen, Lina Yang, Ling Peng, Xiang Li, Tianhe Chi

In this paper, we proposed a directionally constrained fully convolutional neural network (D-FCN) that can take the original 3D coordinates and LiDAR intensity as input; thus, it can directly apply to unstructured 3D point clouds for semantic labeling.

General Classification Line Detection +1

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