Latent transformations neural network for object view synthesis

Latent transformations neural network for object view synthesis

Sangpil Kim, Nick Winovich, Hyung-Gun Chi, Guang Lin, Karthik Ramani
The Visual Computer (2019): 1-15.

We propose a fully convolutional conditional generative neural network, the latent transformation neural network, capable of rigid and non-rigid object view synthesis using a lightweight architecture suited for real-time applications and embedded...

read more
GhostAR: A Time-space Editor for Embodied Authoring of Human-Robot Collaborative Task with Augmented Reality

GhostAR: A Time-space Editor for Embodied Authoring of Human-Robot Collaborative Task with Augmented Reality

Yuanzhi Cao*, Tianyi Wang*, Xun Qian, Pawan S. Rao, Manav Wadhawan, Ke Huo, Karthik Ramani
Proceedings of the 32nd Annual Symposium on User Interface Software and Technology. ACM, 2019.

We present GhostAR, a time-space editor for authoring and acting Human-Robot-Collaborative (HRC) tasks in-situ. Our system adopts an embodied authoring approach in Augmented Reality (AR), for spatially editing the actions and programming the robots...

read more
Collaboration Requirement Planning Protocol for HUB-CI in Factories of the Future

Collaboration Requirement Planning Protocol for HUB-CI in Factories of the Future

P.O. Dusadeerungsikul, M. Sreeram, X. He, A. Nair, K. Ramani, A.J. Quinn, S.Y. Nof
Procedia Manufacturing, ICPR-25, Chicago, IL August 2019

Rapid advances in production systems’ models and technology continually challenge manufacturers preparing for the factories of the future. To address the complexity issues typically coupled with the improvements, we have developed a brain-inspired...

read more
V.Ra: An In-Situ Visual Authoring System for Robot-IoT Task Planning with Augmented Reality

V.Ra: An In-Situ Visual Authoring System for Robot-IoT Task Planning with Augmented Reality

Yuanzhi Cao, Zhuangying Xu, Fan Li, Wentao Zhong, Ke Huo, and Karthik Ramani
In Proceedings of the 2019 on Designing Interactive Systems Conference (pp. 1059-1070). ACM.

We present V.Ra, a visual and spatial programming system for robot-IoT task authoring. In V.Ra, programmable mobile robots serve as binding agents to link the stationary IoTs and perform collaborative tasks. We establish an ecosystem that...

read more
V.Ra: An In-Situ Visual Authoring System for Robot-IoT Task Planning with Augmented Reality

V.Ra: An In-Situ Visual Authoring System for Robot-IoT Task Planning with Augmented Reality

Yuanzhi Cao, Zhuangying Xu, Fan Li, Wentao Zhong, Ke Huo, and Karthik Ramani
Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems, LBW0151:1–LBW0151:6. https://doi.org/10.1145/3290607.3312797

We present V.Ra, a visual and spatial programming system for robot-IoT task authoring. In V.Ra, programmable mobile robots serve as binding agents to link the stationary IoTs and perform collaborative tasks. We establish an ecosystem that...

read more
Shape Structuralizer: Design, Fabrication, and User-driven Iterative Refinement of 3D Mesh Models

Shape Structuralizer: Design, Fabrication, and User-driven Iterative Refinement of 3D Mesh Models

Subramanian Chidambaram, Yunbo Zhang, Venkatraghavan Sundararajan, Niklas Elmqvist, and Karthik Ramani
ACM SIGCHI Conference on Human Factors in Computing Systems (CHI 2019), May 4–9, 2019, Glasgow, Scotland, UK

Current Computer-Aided Design (CAD) tools lack proper support for guiding novice users towards designs ready for fabrication. We propose Shape Structuralizer (SS), an interactive design support system that repurposes surface models into structural...

read more
Deep Learning 3D Shapes Using ALT-AZ Anisotropic 2-Sphere Convolution

Deep Learning 3D Shapes Using ALT-AZ Anisotropic 2-Sphere Convolution

Liu, Min, Fupin Yao, Chiho Choi, Sinha Ayan, and Karthik Ramani
In proceedings of Seventh International Conference on Learning Representations (ICLR), New Orleans, May 6-9, 2019

The ground-breaking performance obtained by deep convolutional neural networks (CNNs) for image processing tasks is inspiring research efforts attempting to extend it for 3D geometric tasks. One of the main challenge in applying CNNs to 3D shape...

read more