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Hao Su

Researcher at University of California, San Diego

Publications -  364
Citations -  82843

Hao Su is an academic researcher from University of California, San Diego. The author has contributed to research in topics: Computer science & Point cloud. The author has an hindex of 57, co-authored 302 publications receiving 55902 citations. Previous affiliations of Hao Su include Philips & Jiangxi University of Science and Technology.

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Journal ArticleDOI

Unsupervised texture transfer from images to model collections

TL;DR: The method allows for large-scale unsupervised production of richly textured 3D models directly from image data, providing high quality virtual objects for 3D scene design or photo editing applications, as well as a wealth of data for training machine learning algorithms for various inference tasks in graphics and vision.
Journal ArticleDOI

A Concentric Tube Continuum Robot with Piezoelectric Actuation for MRI-Guided Closed-Loop Targeting

TL;DR: As the first of its kind, MRI-guided targeted concentric tube needle placements with ex vivo porcine liver are demonstrated with 4.64 mm RMS error through closed-loop control of the piezoelectrically-actuated robot.
Proceedings ArticleDOI

Teleoperation system with hybrid pneumatic-piezoelectric actuation for MRI-guided needle insertion with haptic feedback

TL;DR: A surgical master-slave tele-operation system for percutaneous interventional procedures under continuous magnetic resonance imaging (MRI) guidance and a pneumatically actuated haptic master robot is developed to render force associated with needle placement interventions to the clinician.
Posted Content

View Extrapolation of Human Body from a Single Image

TL;DR: In this article, a shape estimation network and an image generation network are combined to synthesize novel views of human body from a single image, and at the interface a perspective transformation is applied to generate a forward flow for pixel value transportation.
Journal ArticleDOI

Progress in robotics for combating infectious diseases.

TL;DR: In this paper, the fundamental requirements for robotics for infectious disease management and outline how robotic technologies can be used in different scenarios, including disease prevention and monitoring, clinical care, laboratory automation, logistics, and maintenance of socioeconomic activities.