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Open-Vocabulary Instance Segmentation for Scene Understanding in Mobile Robots

This repository contains the implementation of an open-vocabulary semantic mapping pipeline based on TALOS and Voxeland. By leveraging the capabilities of LVLMs and category-agnostic segmentation models, TALOS manages to provide a rich semantic descriptions of individual images, unconstrained by the categories which exist on any particular training dataset. These open-vocabulary object detections are integrated over time into a persistent coherent map in Voxeland, which uses a probabilistic voxel-based representation to combine the different detections and represent both the geometry and the semantic categories present in the scene.

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Please see the individual repos for TALOS and Voxeland for detailed instructions.

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