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Starred repositories
Minimal, robust, accurate and real-time LiDAR odometry
Work in progress repository for the future course on Fundamentals of Computing for Robotics, Graphics and Computer Vision of the Master in Robotics, Graphics and Computer Vision of the University o…
A list of papers about point clouds registration
A Modular Framework for LiDAR-based Lifelong Mapping
Universal Monocular Metric Depth Estimation
Official implementation for the paper "Deep ViT Features as Dense Visual Descriptors".
A tightly coupled and real time LiDAR-Inertial SLAM algorithm. Based upon LIMO-Velo and FAST_LIO projects.
A LiDAR-based complete global localization method.
Asynchronous Multiple LiDAR-Inertial Odometry using Point-wise Inter-LiDAR Uncertainty Propagation
This is the repository for HeLiPR file player.
Python scripts performing Metric Monocular Depth Estimation using the Unidepth model in ONNX.
Collection of Papers with Codes: LiDAR Odometry/SLAM, Dynamic Object Removal, and Multiple Map Merging
[ECCV 2024 - Oral] ACE0 is a learning-based structure-from-motion approach that estimates camera parameters of sets of images by learning a multi-view consistent, implicit scene representation.
Ocean is the in-house framework for Computer Vision (CV) and Augmented Reality (AR) applications at Meta. It is platform independent and is mainly implemented in C/C .
Any-Feature V-SLAM is an automated visual SLAM library for Monocular cameras capable of switching to a chosen type of feature effortlessly and without manual intervention.
[ICRA'24] DeFlow: Decoder of Scene Flow Network in Autonomous Driving
From Correspondences to Pose: Non-minimal Certifiably Optimal Relative Pose without Disambiguation (CVPR 2024 - Highlight)
Joinied Positioning and Control Model Based on Factor Graph Optimization (FGO)
ROS2 / FAST_LIO / PGO / Online Re-Localization / Consistent Map with BA or HBA
Machine Learning use in edge and corner detection in point clouds
Depth Anything V2. A More Capable Foundation Model for Monocular Depth Estimation