SalCrop: Spatio-temporal Saliency Based Video Cropping

被引:1
|
作者
Zhang, Kao [1 ]
Shang, Yan [2 ]
Li, Songnan [2 ]
Liu, Shan [3 ]
Chen, Zhenzhong [1 ]
机构
[1] Wuhan Univ, Wuhan, Peoples R China
[2] Tencent Media Lab, Tencent, Peoples R China
[3] Tencent Amer, Tencent Media Lab, Palo Alto, CA USA
关键词
Video cropping; video saliency; video editing; deep learning;
D O I
10.1109/VCIP56404.2022.10008849
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Video cropping is a key research task in video processing field. In this paper, a spatio-temporal saliency based video cropping framework (SalCrop) is introduced including four core modules: video scene detection module, video saliency prediction module, adaptive cropping module, and video codec module. It can automatically reframe videos in the desired aspect ratios. In addition, a large-scale video cropping dataset (VCD) is built for training and testing. Experiments on the VCD test dataset show that our SalCrop outperforms the state-of-the-art algorithms with high efficiency. Besides, a FFmpeg video filter is developed based on the framework, which can be widely used in different scenarios. A demo is available at: https://mme.tencent.com/smartcontent/videoCrop (access token: test token).
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页数:1
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