6 citations · 21 across the 13 of their papers we have counts for
7 papers · 1 filter
NeRF-SLAM: Real-Time Dense Monocular SLAM with Neural Radiance Fields
Antoni Rosinol, John J. Leonard, Luca Carlone
We propose a novel geometric and photometric 3D mapping pipeline for accurate and real-time scene reconstruction from monocular images. To achieve this, we leverage recent advances…
Probabilistic Volumetric Fusion for Dense Monocular SLAM
Antoni Rosinol, John J. Leonard, Luca Carlone
We present a novel method to reconstruct 3D scenes from images by leveraging deep dense monocular SLAM and fast uncertainty propagation. The proposed approach is able to 3D reconst…
Lidar-Monocular Surface Reconstruction Using Line Segments
Victor Amblard, Timothy P. Osedach, Arnaud Croux +2
Structure from Motion (SfM) often fails to estimate accurate poses in environments that lack suitable visual features. In such cases, the quality of the final 3D mesh, which is con…
A Front-End for Dense Monocular SLAM using a Learned Outlier Mask Prior
Yihao Zhang, John J. Leonard
Recent achievements in depth prediction from a single RGB image have powered the new research area of combining convolutional neural networks (CNNs) with classical simultaneous loc…
Bootstrapped Self-Supervised Training with Monocular Video for Semantic Segmentation and Depth Estimation
Yihao Zhang, John J. Leonard
For a robot deployed in the world, it is desirable to have the ability of autonomous learning to improve its initial pre-set knowledge. We formalize this as a bootstrapped self-sup…
Self-Supervised Visual Place Recognition Learning in Mobile Robots
Sudeep Pillai, John Leonard
Place recognition is a critical component in robot navigation that enables it to re-establish previously visited locations, and simultaneously use this information to correct the d…