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20242026
most citedOpen-H-Embodiment: A Large-Scale Dataset for Enabling Foundation Models in Medical Robotics

1 citations · 1 across the 1 of their papers we have counts for

collaborators

5 papers

cs.RO20261 cited

Open-H-Embodiment: A Large-Scale Dataset for Enabling Foundation Models in Medical Robotics

Open-H-Embodiment Consortium, :, Nigel Nelson +213

Autonomous medical robots hold promise to improve patient outcomes, reduce provider workload, democratize access to care, and enable superhuman precision. However, autonomous medic…

cs.RO2026

Learning Surgical Robotic Manipulation with 3D Spatial Priors

Yu Sheng, Lidian Wang, Xiaomeng Chu +6

Achieving 3D spatial awareness is crucial for surgical robotic manipulation, where precise and delicate operations are required. Existing methods either explicitly reconstruct the…

cs.CV2025

SpatialSplat: Efficient Semantic 3D from Sparse Unposed Images

Yu Sheng, Jiajun Deng, Xinran Zhang +4

A major breakthrough in 3D reconstruction is the feedforward paradigm to generate pixel-wise 3D points or Gaussian primitives from sparse, unposed images. To further incorporate se…

cs.CV2025

ElectricSight: 3D Hazard Monitoring for Power Lines Using Low-Cost Sensors

Xingchen Li, LiDian Wang, Yu Sheng +6

Protecting power transmission lines from potential hazards involves critical tasks, one of which is the accurate measurement of distances between power lines and potential threats,…

cs.RO2024

MSGField: A Unified Scene Representation Integrating Motion, Semantics, and Geometry for Robotic Manipulation

Yu Sheng, Runfeng Lin, Lidian Wang +5

Combining accurate geometry with rich semantics has been proven to be highly effective for language-guided robotic manipulation. Existing methods for dynamic scenes either fail to…