AI RESEARCH
IRIS-SLAM: Unified Geo-Instance Representations for Robust Semantic Localization and Mapping
arXiv CS.CV
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ArXi:2602.18709v2 Announce Type: replace Geometry foundation models have significantly advanced dense geometric SLAM, yet existing systems often lack deep semantic understanding and robust loop closure capabilities. Meanwhile, contemporary semantic mapping approaches are frequently hindered by decoupled architectures and fragile data association. We propose IRIS-SLAM, a novel RGB semantic SLAM system that leverages unified geometric-instance representations derived from an instance-extended foundation model.