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pro vyhledávání: '"Zhou Xiang-dong"'
This paper presents a new method for end-to-end Video Question Answering (VideoQA), aside from the current popularity of using large-scale pre-training with huge feature extractors. We achieve this with a pyramidal multimodal transformer (PMT) model,
Externí odkaz:
http://arxiv.org/abs/2302.02136
Video question answering (VideoQA) is challenging given its multimodal combination of visual understanding and natural language processing. While most existing approaches ignore the visual appearance-motion information at different temporal scales, i
Externí odkaz:
http://arxiv.org/abs/2205.04061
Autor:
Zhang, Lijun, Zhou, Kangkang, Lu, Feng, Li, Zhenghao, Shao, Xiaohu, Zhou, Xiang-Dong, Shi, Yu
Publikováno v:
In Pattern Recognition February 2025 158
Video question answering (VideoQA) is challenging given its multimodal combination of visual understanding and natural language understanding. While existing approaches seldom leverage the appearance-motion information in the video at multiple tempor
Externí odkaz:
http://arxiv.org/abs/2109.04735
Publikováno v:
IEEE Robotics and Automation Letters, 2021
Recently, the methods based on Convolutional Neural Networks (CNNs) have gained popularity in the field of visual place recognition (VPR). In particular, the features from the middle layers of CNNs are more robust to drastic appearance changes than h
Externí odkaz:
http://arxiv.org/abs/2103.13580
As a spontaneous expression of emotion on face, micro-expression reveals the underlying emotion that cannot be controlled by human. In micro-expression, facial movement is transient and sparsely localized through time. However, the existing represent
Externí odkaz:
http://arxiv.org/abs/2009.09179
Akademický článek
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Autor:
Xu, Rui, Zhou, Jia, Du, Xian-zhi, Zhou, Xiang-dong, Li, Qi, Perelman, Juliy M., Kolosov, Victor P.
Publikováno v:
In Experimental Cell Research 1 September 2019 382(1)
Publikováno v:
In Experimental Cell Research 15 August 2017 357(2):145-154
Publikováno v:
In Neurocomputing 22 March 2017 230:184-196