vMAP: Vectorised Object Mapping for Neural Field SLAM

Figure 1 . vMAP automatically builds an object-level scene model from a real-time RGB-D input stream. Each object is represented by a separate MLP neural field model, all optimised in parallel via vectorised training. We use no 3D shape priors, but the MLP representation encourages object reconstruction to be watertight and complete, even when objects are partially observed or are heavily occluded in the input images. See for instance the separate reconstructions of the armchairs, sofas and cushions, which were mutually occluding each other, in this example from Replica.