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Found 7 papers, 6 papers with code
FM-Fusion: Instance-aware Semantic Mapping Boosted by Vision-Language Foundation Models
Our method achieves 40. 3 mean average precision (mAP) on the ScanNet semantic instance segmentation task.
G3Reg: Pyramid Graph-based Global Registration using Gaussian Ellipsoid Model
Utilizing these GEMs, we then present a distrust-and-verify scheme based on a Pyramid Compatibility Graph for Global Registration (PAGOR).
Pyramid Semantic Graph-based Global Point Cloud Registration with Low Overlap
In this paper, we propose a graph-theoretic framework to address the problem of global point cloud registration with low overlap.
A Registration-aided Domain Adaptation Network for 3D Point Cloud Based Place Recognition
In the field of large-scale SLAM for autonomous driving and mobile robotics, 3D point cloud based place recognition has aroused significant research interest due to its robustness to changing environments with drastic daytime and weather variance.
End-to-End 3D Point Cloud Learning for Registration Task Using Virtual Correspondences
3D Point cloud registration is still a very challenging topic due to the difficulty in finding the rigid transformation between two point clouds with partial correspondences, and it's even harder in the absence of any initial estimation information.
SeasonDepth: Cross-Season Monocular Depth Prediction Dataset and Benchmark under Multiple Environments
Different environments pose a great challenge to the outdoor robust visual perception for long-term autonomous driving, and the generalization of learning-based algorithms on different environments is still an open problem.
DASGIL: Domain Adaptation for Semantic and Geometric-aware Image-based Localization
Long-Term visual localization under changing environments is a challenging problem in autonomous driving and mobile robotics due to season, illumination variance, etc.
