[ICRA24] MoPA: Multi-Modal Prior Aided Domain Adaptation for 3D Semantic Segmentation
☆31Dec 22, 2025Updated 9 months ago
Alternatives and similar repositories for MoPA
Users that are interested in MoPA are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- [ECCV 2024] Reliable Spatial-Temporal Voxels for Multi-Modal Test-Time Adaptation☆19Jan 12, 2026Updated 8 months ago
- Collaborative MCL☆19Sep 3, 2025Updated last year
- 3D LiDAR Mapping in Dynamic Environments using a 4D Implicit Neural Representation (CVPR 2024)☆178Jul 4, 2024Updated 2 years ago
- TASeg: Temporal Aggregation Network for LiDAR Semantic Segmentation (CVPR 2024)☆16Mar 27, 2025Updated last year
- ☆10Aug 16, 2024Updated 2 years ago
- 1-Click AI Models by DigitalOcean Gradient • AdDeploy popular AI models on DigitalOcean Gradient GPU virtual machines with just a single click. Zero configuration with optimized deployments.
- [CVPR 2024 Highlight] LiSA: LiDAR Localization with Semantic Awareness☆59Jun 18, 2024Updated 2 years ago
- ☆20Jul 5, 2023Updated 3 years ago
- Python Package: Fast Ground Segmentation for LiDAR Point Clouds☆38Apr 18, 2025Updated last year
- Source code of NA-LOAM: Normal-based Adaptive LiDAR Odometry and Mapping☆16Aug 17, 2024Updated 2 years ago
- [ICRA 2024] Outram: One-shot Global Localization via Triangulated Scene Graph and Global Outlier Pruning☆179Mar 12, 2024Updated 2 years ago
- ☆45Nov 24, 2024Updated last year
- Code for ICRA 2024 paper "VOLoc: Visual Place Recognition by Querying Compressed Lidar Map"☆56Feb 27, 2024Updated 2 years ago
- This is the code repository for the IEEE-RAL'24 paper "Free-Init: Scan-Free, Motion-Free, and Correspondence-Free Initialization for FMCW…☆21May 29, 2025Updated last year
- Vision-Language Guidance for LiDAR-based Unsupervised 3D Object Detection☆29Nov 21, 2024Updated last year
- Serverless GPU API endpoints on Runpod - Get Bonus Credits • AdSkip the infrastructure headaches. Auto-scaling, pay-as-you-go, no-ops approach lets you focus on innovating your application.
- DiTer: Novel Legged Robot Datasets in Diverse Terrain (accepted in IEEE Sensors Letters'24)