14 papers · 1 filter
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…
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…
Worth Remembering: Surprise-Gated Robot Episodic Memory
Nicolas Gorlo, Derek K. Wise, Alberto Speranzon +1
Robots solving generalist tasks need to be able to ground instructions in their past experience, since humans may refer to notable past events when giving a task (e.g., ``Take me t…
Pandora: Articulated 3D Scene Graphs from Egocentric Vision
Alan Yu, Yun Chang, Christopher Xie +1
Robotic mapping systems typically approach building metric-semantic scene representations from the robot's own sensors and cameras. However, these "first person" maps inherit the r…