Riku Murai (right), a postdoctoral researcher, and Eric Dexheimer (left), a fourth-year PhD student at Imperial College London, are the joint first authors of an innovative new paper that introduces a real-time monocular dense SLAM system. They speak to us ahead of their poster session later today. MASt3R-SLAM: Real-Time Dense SLAM with 3D Reconstruction Priors 8 DAILY CVPR Saturday Highlight Presentation In their paper, Riku and Eric address the challenge of SLAM (Simultaneous Localization and Mapping), which involves estimating the egomotion of a camera – essentially tracking its movement – while simultaneously mapping the 3D geometry of the surrounding scene. “Typically, SLAM, particularly monocular RGB SLAM, where we’re given only images, is hard to do because there are many ambiguous cases,” Riku explains. “Often, people need expertise. You need very careful motion. People typically move the camera in a very specific manner to perform SLAM, so it's not very robust.” While SLAM technology has matured and is now seen as a foundational building block for various robotics and augmented reality products, the need for a plug-and-play solution remains. A significant innovation in this work is the integration of a deep 3D reconstruction prior, known as MASt3R, developed by Naver Labs Europe. This prior is flexible, powerful, and does not require calibration. “Usually, you have an internal team that will calibrate your camera and make sure the hardware-software stack is aligned,” Eric points out. “Having a SLAM system with a single camera
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