R
Rui Huang
Researcher at Google
Publications - 9
Citations - 749
Rui Huang is an academic researcher from Google. The author has contributed to research in topics: Deep learning & Object detection. The author has an hindex of 7, co-authored 9 publications receiving 550 citations. Previous affiliations of Rui Huang include Carnegie Mellon University & China University of Geosciences (Beijing).
Papers
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Proceedings ArticleDOI
Beyond Face Rotation: Global and Local Perception GAN for Photorealistic and Identity Preserving Frontal View Synthesis
TL;DR: Tang et al. as discussed by the authors proposed a Two-Pathway Generative Adversarial Network (TP-GAN) for photorealistic frontal view synthesis by simultaneously perceiving global structures and local details.
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Beyond Face Rotation: Global and Local Perception GAN for Photorealistic and Identity Preserving Frontal View Synthesis
TL;DR: Tang et al. as mentioned in this paper proposed a Two-Pathway Generative Adversarial Network (TP-GAN) for photorealistic frontal view synthesis by simultaneously perceiving global structures and local details.
Posted Content
An LSTM Approach to Temporal 3D Object Detection in LiDAR Point Clouds
Rui Huang,Wanyue Zhang,Abhijit Kundu,Caroline Pantofaru,David A. Ross,Thomas Funkhouser,Alireza Fathi +6 more
TL;DR: This paper proposes a sparse LSTM-based multi-frame 3d object detection algorithm that outperforms the traditional frame by frame approach by 7.5% mAP@0.7 and other multi- frame approaches by 1.2% while using less memory and computation per frame.
Book ChapterDOI
An LSTM Approach to Temporal 3D Object Detection in LiDAR Point Clouds
Rui Huang,Wanyue Zhang,Abhijit Kundu,Caroline Pantofaru,David A. Ross,Thomas Funkhouser,Alireza Fathi +6 more
TL;DR: Li et al. as mentioned in this paper proposed a sparse LSTM-based multi-frame 3D object detection algorithm using a U-Net style 3D sparse convolution network to extract features for each frame's LiDAR point-cloud.
Journal ArticleDOI
A Stable Online Scheduling Strategy for Real-Time Stream Computing Over Fluctuating Big Data Streams
Dawei Sun,Rui Huang +1 more
TL;DR: Experimental results conclusively demonstrate that the SOMG framework has higher potential of providing enhancement on efficient system stability and guaranteeing significant response time.