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• W3138169940 abstract "We show for the first time that a multilayer perceptron (MLP) can serve as the only scene representation in a real-time SLAM system for a handheld RGB-D camera. Our network is trained in live operation without prior data, building a dense, scene-specific implicit 3D model of occupancy and colour which is also immediately used for tracking. Achieving real-time SLAM via continual training of a neural network against a live image stream requires significant innovation. Our iMAP algorithm uses a keyframe structure and multi-processing computation flow, with dynamic information-guided pixel sampling for speed, with tracking at 10 Hz and global map updating at 2 Hz. The advantages of an implicit MLP over standard dense SLAM techniques include efficient geometry representation with automatic detail control and smooth, plausible filling-in of unobserved regions such as the back surfaces of objects." @default.
• W3138169940 created "2021-03-29" @default.
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• W3138169940 date "2021-03-23" @default.
• W3138169940 modified "2023-09-27" @default.
• W3138169940 title "iMAP: Implicit Mapping and Positioning in Real-Time" @default.
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• W3138169940 hasPublicationYear "2021" @default.
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