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Found 6 papers, 0 papers with code
RWT-SLAM: Robust Visual SLAM for Highly Weak-textured Environments
As a fundamental task for intelligent robots, visual SLAM has made great progress over the past decades.
CVFNet: Real-time 3D Object Detection by Learning Cross View Features
In recent years 3D object detection from LiDAR point clouds has made great progress thanks to the development of deep learning technologies.
An Active and Contrastive Learning Framework for Fine-Grained Off-Road Semantic Segmentation
Off-road semantic segmentation with fine-grained labels is necessary for autonomous vehicles to understand driving scenes, as the coarse-grained road detection can not satisfy off-road vehicles with various mechanical properties.
Fine-Grained Off-Road Semantic Segmentation and Mapping via Contrastive Learning
With a set of human-annotated anchor patches, a feature representation is learned to discriminate regions with different traversability, a method of fine-grained semantic segmentation and mapping is subsequently developed for off-road scene understanding.
Off-Road Drivable Area Extraction Using 3D LiDAR Data
We propose a method for off-road drivable area extraction using 3D LiDAR data with the goal of autonomous driving application.
Semantic Segmentation of 3D LiDAR Data in Dynamic Scene Using Semi-supervised Learning
This work studies the semantic segmentation of 3D LiDAR data in dynamic scenes for autonomous driving applications.
Robotics
