3D reconstruction Archivi - Page 3 of 3 - Luigi Freda

Luigi Freda

Robotics & Computer Vision Engineer, PhD

Computer Vision Posts Sensors

21 April 2016 luigi

3D Model Reconstructed from 4 Helmet-held Cameras

Awesome 3D reconstruction and headset. In the 3D reconstruction there are also the meshes of a “sky ceiling”

Sensor-based Exploration Tree (SET) Method

Exploration of Unknown Environments with Robot Manipulators This work presents a method for sensor-based exploration of unknown environments by

Computer Vision Posts

13 April 2016 luigi

Restore 3D Reconstruction

RESTORE: REconStruction with Texture-based Object REfinement https://github.com/NewProggie/Restore “A simple and cost-efficient way of reconstruction real objects is using only a

Business Computer Vision Posts Sensors

9 April 2016 luigi

Holoportation

Simply WOW for this incredible technology from i3D of Microsoft Research. This can capture and present realtime 3D video streams which can

Computer Vision Machine Learning Posts

9 April 2016 luigi

Automatic 2D-to-3D Video Conversion with CNNs

Here you can find details about Deep3D: a system for the automatic conversion of 2D video to 3D video which

Software

pySLAM code: https://github.com/luigifreda/pyslam pySLAM is a visual SLAM pipeline in Python for monocular, stereo, and RGBD cameras. It supports many

Research

My research focuses on robot perception, deep learning, sensor-based motion planning, and control systems. What I love most are computer

Publications

My Google Scholar profile International Journal Papers 3D Multi-Robot Patrolling with a

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Kwang Moo Yi @kwangmoo_yi ·

23 Jan

Paper of the day: Wang et al., "Continuous 3D Perception Model with Persistent State" -- https://cut3r.github.io

RNN state model that can be "read out" as 3D pointmaps.

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Luigi Freda @luigifreda ·

19 Jan

New #pySLAM Upgrades 🚀
📌Incremental #GaussianSplatting during #SLAM using the MonoGS backend.
📌Optimized #Mapping management: Seamlessly generate, save, reload, and browse maps.
📌New #StereoDepthPrediction models.
📌Bug fixes, performance improvements.
https://github.com/luigifreda/pyslam

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