Awesome-LiDAR-MOS

For anyone who wants to do research about 3D point cloud Moving Object Segmentation (MOS)

Continuously updating!

Benchmark

SemanticKITTI: Moving Object Segmentation

Dataset

1. SemanticKITTI (From LMNet)

2. KITTI-Road (From MotionSeg3D)

3. Apollo (From MapMOS)

4. nuScenes (From MapMOS)

5. KITTI-Tracking-19 (From MapMOS)

6. SipailouCampus (From MotionBEV)

Papers

-  Recent papers (from 2019)

Application: out.: outdoor   |   ind.: indoor  

Sensor: pc.: point cloud   |   img.: image   |   rad.: radar

Statistics: 🔥 code is available & stars >= 100  |  ⭐ citation >= 50

2019

• [CRV]Mapless Online Detection of Dynamic Objects in 3D Lidar.[out. pc.] ⭐

2020

• [IROS]Remove, then Revert: Static Point cloud Map Construction using Multiresolution Range Images.[code][out. pc.] 🔥 ⭐

2021

• [RAL]Moving Object Segmentation in 3D LiDAR Data: A Learning-based Approach Exploiting Sequential Data. [code][out. pc.] 🔥 ⭐
• [RAL]ERASOR: Egocentric Ratio of Pseudo Occupancy-Based Dynamic Object Removal for Static 3D Point Cloud Map Building. [code] [out. pc.] 🔥 ⭐
• [RAL]PointMoSeg: Sparse Tensor-Based End-to-End Moving-Obstacle Segmentation in 3-D Lidar Point Clouds for Autonomous Driving.[out. pc.]
• [ECMR]Mapping the Static Parts of Dynamic Scenes from 3D LiDAR Point Clouds Exploiting Ground Segmentation.[out. pc.]

2022

• [TPAMI]Cylindrical and Asymmetrical 3D Convolution Networks for LiDAR-Based Perception.[code] 🔥 ⭐
• [IROS]Efficient Spatial-Temporal Information Fusion for LiDAR-Based 3D Moving Object Segmentation.[code] [out. pc.] 🔥
• [IROS]PUA-MOS: End-to-End Point-wise Uncertainty Weighted Aggregation for Moving Object Segmentation.[code][out. pc.]
• [RAL]RVMOS: Range-View Moving Object Segmentation Leveraged by Semantic and Motion Features.[out. pc.]
• [RAL]Receding Moving Object Segmentation in 3D LiDAR Data Using Sparse 4D Convolutions.[code] [out. pc.] 🔥
• [WACV]Unsupervised 4D LiDAR Moving Object Segmentation in Stationary Settings with Multivariate Occupancy Time Series.[code] [out. pc.]
• [RAL]Automatic Labeling to Generate Training Data for Online LiDAR-Based Moving Object Segmentation.[code] [out. pc.] ⭐

2023

• [IROS]InsMOS: Instance-Aware Moving Object Segmentation in LiDAR Data.[code] [out. pc.] 🔥
• [IROS]LiDAR-SGMOS: Semantics-Guided Moving Object Segmentation with 3D LiDAR.[out. pc.]
• [RAL]Building Volumetric Beliefs for Dynamic Environments Exploiting Map-Based Moving Object Segmentation.[code] [out. pc.] 🔥
• [RAL]MotionBEV: Attention-Aware Online LiDAR Moving Object Segmentation With Bird’s Eye View Based Appearance and Motion Features.[code][out. pc.]
• [RAL]Dynablox: Real-Time Detection of Diverse Dynamic Objects in Complex Environments.[code][out. ind. pc.] 🔥
• [TRO]Radar Instance Transformer: Reliable Moving Instance Segmentation in Sparse Radar Point Clouds.[out. rad.]
• [ICCV]MarS3D: A Plug-and-Play Motion-Aware Model for Semantic Segmentation on Multi-Scan 3D Point Clouds.[code] [out. pc.]
• [Sensors]Real-Time LiDAR Point-Cloud Moving Object Segmentation for Autonomous Driving.[out. pc.]
• [IJAEOG]An efficient image-guided-based 3D point cloud moving object segmentation with transformer-attention in autonomous driving.[out. pc. img.]
• [Arxiv]3D-SeqMOS: A Novel Sequential 3D Moving Object Segmentation in Autonomous Driving.[out. pc.]

2024

• [ICRA]MF-MOS: A Motion-Focused Model for Moving Object Segmentation.[code][out. pc.]
• [Arxiv]RadarMOSEVE: A Spatial-Temporal Transformer Network for Radar-Only Moving Object Segmentation and Ego-Velocity Estimation.[code][out. rad.]
• [Arxiv]SegNet4D: Effective and Efficient 4D LiDAR Semantic Segmentation in Autonomous Driving Environments.[code][out. pc.]