[IROS23] InsMOS: Instance-Aware Moving Object Segmentation in LiDAR Data
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Updated
Jun 5, 2024 - Python
[IROS23] InsMOS: Instance-Aware Moving Object Segmentation in LiDAR Data
A Large-scale Mobile LiDAR Dataset for Semantic Segmentation of Urban Roadways
Point-to-Voxel Knowledge Distillation for LiDAR Semantic Segmentation (CVPR 2022)
Official PyTorch implementation of Superpoint Transformer introduced in [ICCV'23] "Efficient 3D Semantic Segmentation with Superpoint Transformer" and SuperCluster introduced in [3DV'24 Oral] "Scalable 3D Panoptic Segmentation As Superpoint Graph Clustering"
Achelous: A Fast Unified Water-surface Panoptic Perception Framework based on Fusion of Monocular Camera and 4D mmWave Radar
Semantic Segmentation of Images and Point Clouds for Traversability Estimation
Fast and memory efficient semantic segmentation of 3D point clouds. Runs on Windows, Mac and Linux.
Implementing a PointNet based architecture for classification and segmentation with point clouds. Q1 and Q2 focus on implementing, training and testing models. Q3 asks you to quantitatively analyze model robustness.
3D LiDAR Semantic Segmentation with range images and Retentive Networks
3D Teeth Scan Segmentation via Rotation-Invariant Descriptor
Point Cloud Segmentation Using PointNet
Official Pytorch implementation of paper: "SPoVT: Semantic-Prototype Variational Transformer for Dense Point Cloud Semantic Completion"
3D Human Part Segmentation with Point Transformer
The repo proposes a pipeline for indoor mapping by use of 3D meshes from MVS RGB images and conversion into point clouds for segmentation.
Final project titled "Point Cloud Segmentation and Object Tracking using RGB-D Data" for the Machine Vision (EE 576) course.
[CVPR'23] OpenScene: 3D Scene Understanding with Open Vocabularies
Deep Learning for Computer Vision 深度學習於電腦視覺 by Frank Wang 王鈺強
[CVPR'22 Best Paper Finalist] Official PyTorch implementation of the method presented in "Learning Multi-View Aggregation In the Wild for Large-Scale 3D Semantic Segmentation"
Implementation of point transformer for point cloud classification and segmentation
Code for the SIGGRAPH 2022 paper "DeltaConv: Anisotropic Operators for Geometric Deep Learning on Point Clouds."
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