22 papers
3D Scene Graph Prediction: Generating Hierarchical Models from Partially Observed Environments
Siyi Hu, Siyi H, Jared Strader +3
Generating realistic 3D indoor scenes is an area of growing interest in computer vision and robotics. Existing methods, often motivated by applications such as interior design, gen…
Hydra++: Real-Time Hierarchical 3D Scene Graph Construction With Object-Level Shape Estimation
Hyungtae Lim, Nathan Hughes, Xihang Yu +5
3D scene graphs provide a hierarchical abstraction of environments by encoding spatial entities, such as objects and places, and their relationships. However, existing scene graph…
3D Scene Graphs: Open Challenges and Future Directions
Dennis Rotondi, Francesco Argenziano, Sebastian Koch +10
3D Scene Graphs (3DSGs) have emerged as a powerful representation for spatial AI by combining geometric grounding with semantic and relational abstractions of the environment. Thei…
FOUND-IT: Foundation-model-first Task-driven 3D Scene Graphs with Granularity on Demand
Dominic Maggio, Nicolas Gorlo, Kris Hauser +1
We present the first approach to build hierarchical task-driven 3D scene graphs of arbitrary indoor or outdoor environments using an uncalibrated monocular camera in real-time. We…
Language as a Sensor: Calibrated Spatial Belief Estimation in 3D Scenes from Natural Language
Aryan Naveen, Jason Xinyu Liu, Luca Carlone +1
Robots deployed in human-centric environments routinely receive natural-language descriptions of spatial information ("I left my backpack on the table") that reference parts of the…
Remember with Confidence: Uncertainty Quantification for Spatio-temporal Memory with Probabilistic Guarantees
Harry Zhang, Nicolas Gorlo, Luca Carlone
Long-horizon robot operation requires spatio-temporal memory to record the environment state and recall it for downstream reasoning. Scene graphs and retrieval-augmented systems gr…