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Luigi Freda

Robotics & Computer Vision Engineer, PhD

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place recognition

Computer VisionMachine LearningMixed RealityPerceptionPostsRobotics
luigi 22 August 201622 August 2016 0 Comments 3D reconstruction, augmented reality, machine-learning, mapping, open source, place recognition, robotics, SLAM, visual localization

ElasticFusion – Real-time Light Source Detection

A new journal paper about ElasticFusion has come out from Davison’s group. New exciting results on 3D light source mapping are presented.

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BusinessComputer VisionPostsSensors
luigi 16 May 201616 May 2016 0 Comments 3D reconstruction, computer vision, mapping, place recognition, sensors, SLAM, visual localization

Google New Plan: Map the Interior World in 3-D

Everyone knows about Google Map and use it. But now the internet giant has a bigger target: it wants to digitally map

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Computer VisionPostsRobotics
luigi 23 April 201625 August 2016 0 Comments 3D reconstruction, computer vision, dataset, features, mapping, open source, place recognition, SLAM, visual localization

Stereo ORB-SLAM2 in the EuRoC MAV Dataset

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Computer VisionMachine LearningPosts
luigi 11 April 201613 April 2016 0 Comments computer vision, gps, place recognition, visual localization

Visual localization, a potential alternative for GPS

A potential alternative for GPS. “PoseNet, is able to estimate your location and orientation from a single colour image. It

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News About Me

  • 3DMR – 3D Multi-Robot Exploration with a Two-Level Coordination Strategy and Prioritization
  • My new pySLAM v2 is out!
  • Member of the Program Committee of SAC 2020-IRMAS Track
  • PLVS for Circus Maximus Mixed-Reality Experience
  • Visual Perception and Spatial Computing

Blog

  • 3DMR – 3D Multi-Robot Exploration with a Two-Level Coordination Strategy and Prioritization
  • My new pySLAM v2 is out!
  • ROSIntegration for Unreal Engine 4.23
  • PLVS for Circus Maximus Mixed-Reality Experience
  • Visual Perception and Spatial Computing

Tags

2D to 3D 3D reconstruction augmented reality business CNN computer vision data analysis dataset deep-learning disaster robotics drones energy features gps image processig inertial lidar machine-learning mapping math multi-robot NN open source perception place recognition robotics self-driving car sensor-based motion planning sensors SLAM TRADR UGVs USAR visual localization visual servoing VR

Tweets

Retweet on Twitter Luigi Freda Retweeted
holynski_ Aleksander Holynski @holynski_ ·
15 Sep

Check out our new paper that turns a (single image) => (interactive dynamic scene)!

I’ve had so much fun playing around with this demo.

Try it out yourself on the website: http://generative-dynamics.github.io/

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Retweet on Twitter Luigi Freda Retweeted
gkopanas Georgios Kopanas @gkopanas ·
4 Sep

The most important factor that determines the quality of a reconstruction is not the actual NeRF variant you are using but rather where you place the cameras.

We give insights on practical ways to solve this problem in realistic environments.

https://arxiv.org/abs/2309.00014

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