ICRA-2020-point-cloud-analysis

ICRA 2020 papers focusing on point cloud analysis

• Spatio-Temporal Non-Rigid Registration of 3D Point Clouds of Plants

  • [Code]

• Lidar-Monocular Visual Odometry Using Point and Line Features

• PointAtrousGraph: Deep Hierarchical Encoder-Decoder with Point Atrous Convolution for Unorganized 3D Points

• SegVoxelNet: Exploring Semantic Context and Depth-Aware Features for 3D Vehicle Detection from Point Cloud

• SegVoxelNet: Exploring Semantic Context and Depth-Aware Features for 3D Vehicle Detection from Point Cloud

• Highly Parallelizable Plane Extraction for Organized Point Clouds Using Spherical Convex Hulls

• CNN-Based Lidar Point Cloud De-Noising in Adverse Weather

• PointNet++ Grasping: Learning an End-To-End Spatial Grasp Generation Algorithm from Sparse Point Clouds

• Modeling of Architectural Components for Large-Scale Indoor Spaces from Point Cloud Measurement

• Modeling of Architectural Components for Large-Scale Indoor Spaces from Point Cloud Measurement

• Modeling of Architectural Components for Large-Scale Indoor Spaces from Point Cloud Measurement

• Learning to Optimally Segment Point Clouds

• Learning to Optimally Segment Point Clouds

• Learning to Optimally Segment Point Clouds

• Robust Method for Removing Dynamic Objects from Point Clouds

• Robust Method for Removing Dynamic Objects from Point Clouds

• Any Motion Detector: Learning Class-Agnostic Scene Dynamics from a Sequence of LiDAR Point Clouds

• PointTrackNet: An End-To-End Network for 3-D Object Detection and Tracking from Point Clouds