ToolDex: An Ego-Exo Human Demonstration Dataset for Creative Physical Tool Use
Overview
This paper introduces ToolDex, a large-scale dataset featuring synchronized egocentric and exocentric camera recordings of humans selecting, adapting, and repurposing objects as tools. The dataset includes high-fidelity multi-view observations and rich annotations for hands, tools, target objects, and deformable interactions. It also establishes a benchmark suite evaluating physical tool-use reasoning, sparse-view 3D and 4D reconstruction, and robot policy learning capabilities.
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Dataset · modalities: egocentric-exocentric · Differing source assertions
“ol-use behavior with sufficient scale, fidelity, and diversity. Existing benchmarks are often simulation-based, focus on simplified interactions, or lack detailed observations and annotations. We introduce ToolDex, a large-scale egocentric-exocentric (ego-exo) human demonstration dataset for creative physical tool use. ToolDex captures scenarios in which humans select, adapt, and repurpose available objects as tools.”
Exact source · revision 1Source owner not reported
Dataset · modalities: hands · Differing source assertions
“Using synchronized egocentric cameras and eight exocentric cameras, the dataset provides high-fidelity multi-view observations and rich annotations for hands, tools, target objects, and their deformable interactions. Beyond data collection, we establish a benchmark suite characterizing three core capabilities: physical tool-use reasoning, sparse-view 3D and 4D reconstruction, and robot policy learning. ToolDex provi”
Exact source · revision 1Source owner not reported
Dataset · modalities: tools · Differing source assertions
“Using synchronized egocentric cameras and eight exocentric cameras, the dataset provides high-fidelity multi-view observations and rich annotations for hands, tools, target objects, and their deformable interactions. Beyond data collection, we establish a benchmark suite characterizing three core capabilities: physical tool-use reasoning, sparse-view 3D and 4D reconstruction, and robot policy learning. ToolDex provi”
Exact source · revision 1Source owner not reported
Dataset · modalities: target objects · Differing source assertions
“Using synchronized egocentric cameras and eight exocentric cameras, the dataset provides high-fidelity multi-view observations and rich annotations for hands, tools, target objects, and their deformable interactions. Beyond data collection, we establish a benchmark suite characterizing three core capabilities: physical tool-use reasoning, sparse-view 3D and 4D reconstruction, and robot policy learning. ToolDex provi”
Exact source · revision 1Source owner not reported
Dataset · tasks: physical tool-use reasoning · Differing source assertions
“Using synchronized egocentric cameras and eight exocentric cameras, the dataset provides high-fidelity multi-view observations and rich annotations for hands, tools, target objects, and their deformable interactions. Beyond data collection, we establish a benchmark suite characterizing three core capabilities: physical tool-use reasoning, sparse-view 3D and 4D reconstruction, and robot policy learning. ToolDex provi”
Exact source · revision 1Source owner not reported
Dataset · tasks: sparse-view 3D and 4D reconstruction · Differing source assertions
“Using synchronized egocentric cameras and eight exocentric cameras, the dataset provides high-fidelity multi-view observations and rich annotations for hands, tools, target objects, and their deformable interactions. Beyond data collection, we establish a benchmark suite characterizing three core capabilities: physical tool-use reasoning, sparse-view 3D and 4D reconstruction, and robot policy learning. ToolDex provi”
Exact source · revision 1Source owner not reported
Dataset · tasks: robot policy learning · Differing source assertions
“Using synchronized egocentric cameras and eight exocentric cameras, the dataset provides high-fidelity multi-view observations and rich annotations for hands, tools, target objects, and their deformable interactions. Beyond data collection, we establish a benchmark suite characterizing three core capabilities: physical tool-use reasoning, sparse-view 3D and 4D reconstruction, and robot policy learning. ToolDex provi”
Exact source · revision 1Source owner not reported
Dataset · embodiments: human demonstration
“ToolDex: An Ego-Exo Human Demonstration Dataset for Creative Physical Tool Use”
Exact source · revision 1Source owner not reported
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- arXiv Robotics — research abstractsSignalToolDex: An Ego-Exo Human Demonstration Dataset for Creative Physical Tool Use
This paper introduces ToolDex, a large-scale dataset featuring synchronized egocentric and exocentric camera recordings of humans selecting, adapting, and repurposing objects as tools. The dataset includes high-fidelity multi-view observations and rich annotations for hands, tools, target objects, and deformable interactions. It also establishes a benchmark suite evaluating physical tool-use reasoning, sparse-view 3D and 4D reconstruction, and robot policy learning capabilities.
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