I presented our work: "REACT: Real-time Efficient Attribute Clustering and Transfer for Updatable 3D Scene Graph" at IROS 2025 in Hangzhou, China

Modern-day autonomous robots need high-level map representations to perform sophisticated tasks. Recently, 3D scene graphs (3DSGs) have emerged as a promising al- ternative to traditional grid maps, blending efficient memory use and rich feature representation. However, most efforts to apply them have been limited to static worlds. This work introduces REACT, a framework that efficiently performs real- time attribute clustering and transfer to relocalize object nodes in a 3DSG. REACT employs a novel method for comparing object instances using an embedding model trained on triplet loss, facilitating instance clustering and matching. Experimental results demonstrate that REACT is able to relocalize ob- jects while maintaining computational efficiency. The REACT framework’s source code will be available as an open-source project, promoting further advancements in reusable and up- datable 3DSGs