SalCrop: Spatio-temporal Saliency Based Video Cropping

Kao Zhang, Yan Shang, Songnan Li, Shan Liu, Zhenzhong Chen

Abstract: 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).