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Computational Visual Media

Computational Visual Media is a Single-Blinded peer-reviewed open access journal published quarterly by Tsinghua University Press and Springer under the SpringerOpen brand. It publishes original high-quality research papers and significant review articles on novel ideas, methods, and systems relevant to visual media.

Current Issue: Volume 6, Issue 4 (2020)

Research Articles

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A survey of recent interactive image segmentation methods
Hiba Ramadan, Chaymae Lachqar, and Hamid Tairi

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Kernel-blending connection approximated by a neural network for image classification
Xinxin Liu, Yunfeng Zhang, Fangxun Bao, Kai Shao, Ziyi Sun, and Caiming Zhang

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A new dataset of dog breed images and a benchmark for fine-grained classification
Ding-Nan Zou, Song-Hai Zhang, Tai-Jiang Mu, and Min Zhang

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Weight asynchronous update: Improving the diversity of filters in a deep convolutional network
Dejun Zhang, Linchao He, Mengting Luo, Zhanya Xu, and Fazhi He

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Computing knots by quadratic and cubic polynomial curves
Fan Zhang, Jinjiang Li, Peiqiang Liu, and Hui Fan

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Fluid-inspired field representation for risk assessment in road scenes
Xuanpeng Li, Lifeng Zhu, Qifan Xue, Dong Wang, and Yongjie Jessica Zhang

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Temporal scatterplots
Or Patashnik, Min Lu, Amit H. Bermano, and Daniel Cohen-Or

Computational Visual Media cover