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Xiaopeng Zhang
Researcher at Qualcomm
Publications - 9
Citations - 513
Xiaopeng Zhang is an academic researcher from Qualcomm. The author has contributed to research in topics: Multispectral image & RGB color model. The author has an hindex of 9, co-authored 9 publications receiving 436 citations.
Papers
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Proceedings ArticleDOI
Near-infrared guided color image dehazing
TL;DR: An improved image dehazing scheme using a pair of color and NIR images, which effectively estimates the airlight color and transfers details from the NIR, and can achieve substantial improvements on the detail recovery and the color distribution over the existing imageDehazing algorithms.
Proceedings ArticleDOI
A Quantization-Friendly Separable Convolution for MobileNets
TL;DR: Zhang et al. as mentioned in this paper proposed a quantization-friendly separable convolution architecture, which can effectively offload GPU and make it possible to deploy DL on fixed-point pipeline.
Patent
Multispectral eye analysis for identity authentication
TL;DR: In this article, the authors proposed a method for generating high resolution iris templates and detecting spoofs, enabling more reliable and secure iris authentication using RGB and NIR images.
Proceedings ArticleDOI
A Quantization-Friendly Separable Convolution for MobileNets
TL;DR: This work analyzed the root cause of quantization loss and proposed a quantization-friendly separable convolution architecture that can archive 8-bit inference top-1 accuracy and almost closed the gap to the float pipeline.
Journal ArticleDOI
Low-Power Computer Vision: Status, Challenges, and Opportunities
Sergei Alyamkin,Matthew Ardi,Alexander C. Berg,Achille Brighton,Bo Chen,Yi Chen,Hsin-Pai Cheng,Zichen Fan,Chen Feng,Bo Fu,Kent Gauen,Abhinav Goel,Alexander Goncharenko,Xuyang Guo,Soonhoi Ha,Andrew Howard,Xiao Hu,Yuanjun Huang,Dong-Hyun Kang,Jaeyoun Kim,Jong-Gook Ko,Alexander Kondratyev,Jun-Hyeok Lee,Seungjae Lee,Suwoong Lee,Zichao Li,Zhiyu Liang,Juzheng Liu,Xin Liu,Yang Lu,Yung-Hsiang Lu,Deeptanshu Malik,Hong Hanh Nguyen,Eunbyung Park,Denis Repin,Liang Shen,Tao Sheng,Fei Sun,David Svitov,George K. Thiruvathukal,Baiwu Zhang,Jingchi Zhang,Xiaopeng Zhang,Shaojie Zhuo +43 more
TL;DR: The state of the art for low-power solutions to detect objects in images is examined to suggest directions for research as well as opportunities forLow-power computer vision.