Probing the 3D Awareness of Visual Foundation Models
As visual foundation models increasingly find their way into SLAM and 3D reconstruction pipelines, an important question arises: are these
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Luigi Freda
Computer Vision, AI, Robotics Engineer, PhD
visual localization
pySLAM v.2.10.0 – A Hybrid Python/C++ Framework for Visual SLAM and 3D Perception
I’m happy to share pySLAM v2.10.0 🎉 🔗 https://github.com/luigifreda/pyslam This is a major update that moves the project forward on
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Figure AI Announces Helix 02 – a General-Purpose Humanoid System
Figure AI has announced Helix 02, a new AI control system for its humanoid robots, detailed in a post published
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RSS 2025 Workshop: Unifying Visual SLAM – From Fragmented Datasets to Scalable, Real-World Solutions
Excited to share Prof. Michael Milford’s post about the upcoming “Unifying Visual SLAM: From Fragmented Datasets to Scalable, Real-World Solutions”
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A new release of pySLAM is here. Loop-closing, volumetric integration, depth prediction and more improvements.
🎉 pySLAM v2.2.5 is here! This new release includes a visual SLAM pipeline for monocular, stereo, and RGBD cameras with:
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pySLAM v2.1 is out
I am happy to share the new version of pyslam: v2.1. It comes with new improvements and the following new
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PLVS code released
I am happy to release the code of my project PLVS. PLVS is a real-time system that leverages sparse RGB-D and Stereo SLAM, volumetric mapping, and
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slamplay is ready!
If you love to play with SLAM like me, I shared slamplay on github: https://github.com/luigifreda/slamplay. slamplay is a collection of powerful
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My new pySLAM v2 is out!
I am excited to release pySLAM v2. The new version allows you to play with SLAM techniques, visual-odometry, keyframes, bundle-adjustment,
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PLVS for Circus Maximus Mixed-Reality Experience
If you are visiting Rome, now you can go to the Circus Maximus and enjoy a great Mixed-Reality experience. An
Read morePLVS: An open-source SLAM system with Points, Lines, Volumetric mapping and 3D incremental Segmentation
PLVS(*) is a real-time system that leverages sparse RGB-D and Stereo SLAM, volumetric mapping, and 3D unsupervised incremental segmentation. PLVS
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CNN-SLAM: Real-time dense monocular SLAM with learned depth prediction
In this page, the Authors K. Tateno, F. Tombari, I. Laina and N. Navab present the following paper in which CNNs are used
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RGBDTAM: A Cost-Effective and Accurate RGB-D Tracking and Mapping System
In this post, Alejo Concha Belenguer presents his new work RGBDTAM. This is a direct SLAM pipeline that runs in real-time and
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Microsoft HoloLens brings New Vision to Elevator Maintenance of Thyssenkrupp
Using Microsoft HoloLens, 24,000+ service technicians of Thyssenkrupp will be able to visualize and identify problems with elevators ahead of
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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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