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- Tsinghua UniversityCN44 papers
- Xi'an Jiaotong UniversityCN44 papers
- Chinese Academy of SciencesCN40 papers
- Northwestern Polytechnical UniversityCN34 papers
- Peking UniversityCN34 papers
- Shanghai Jiao Tong UniversityCN29 papers
- Nanyang Technological UniversitySG28 papers
- Sun Yat-sen UniversityCN26 papers
- University of Chinese Academy of SciencesCN25 papers
- Zhejiang UniversityCN22 papers
- Southeast UniversityCN21 papers
- Beijing University of Posts and TelecommunicationsCN19 papers
25 papers · 2 filters
A Gated Peripheral-Foveal Convolutional Neural Network for Unified Image Aesthetic Prediction
Xiaodan Zhang, Xinbo Gao, Wen Lu +1
Learning fine-grained details is a key issue in image aesthetic assessment. Most of the previous methods extract the fine-grained details via random cropping strategy, which may un…
Attention-Mechanism-based Tracking Method for Intelligent Internet of Vehicles
Xu Kang, Bin Song, Jie Guo +2
Vehicle tracking task plays an important role on the internet of vehicles and intelligent transportation system. Beyond the traditional GPS sensor, the image sensor can capture dif…
Vehicle Tracking Using Surveillance with Multimodal Data Fusion
Yue Zhang, Bin Song, Xiaojiang Du +1
Vehicle location prediction or vehicle tracking is a significant topic within connected vehicles. This task, however, is difficult if only a single modal data is available, probabl…
Object Tracking in Hyperspectral Videos with Convolutional Features and Kernelized Correlation Filter
Kun Qian, Jun Zhou, Fengchao Xiong +2
Target tracking in hyperspectral videos is a new research topic. In this paper, a novel method based on convolutional network and Kernelized Correlation Filter (KCF) framework is p…
PIRM Challenge on Perceptual Image Enhancement on Smartphones: Report
Andrey Ignatov, Radu Timofte, Thang Van Vu +45
This paper reviews the first challenge on efficient perceptual image enhancement with the focus on deploying deep learning models on smartphones. The challenge consisted of two tra…
Pyramidal Person Re-IDentification via Multi-Loss Dynamic Training
Feng Zheng, Cheng Deng, Xing Sun +5
Most existing Re-IDentification (Re-ID) methods are highly dependent on precise bounding boxes that enable images to be aligned with each other. However, due to the challenging pra…