Article

Language Sensor Model: Estimating 3D Scene Spatial Beliefs from Natural Language and Fusing with Perception

The authors propose the Language Sensor Model (LSM), which maps each natural language description and its scene-graph context to a multimodal distribution, using mixture weights to represent referential ambiguity and component covariances to represent spatial uncertainty.

Part of the event: LSM converts language descriptions into calibrated spatial distributions and integrates them into VL-Map mapping

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