Utilization of event-based cameras is expected to improve the visual quality of video frame interpolation solutions. We introduce a learning-based method to exploit moving region boundaries in a video sequence to increase the overall interpolation quality.Event cameras allow us to determine moving areas precisely; and hence, better video frame interpolation quality can be achieved by emphasizing these regions using an appropriate loss function. The results show a notable average \textit{PSNR} improvement of $1.3$ dB for the tested data sets, as well as subjectively more pleasing visual results with less ghosting and blurry artifacts.
翻译：利用事件相机可望提高视频框架内插解决方案的视觉质量。 我们引入了一种基于学习的方法,在视频序列中利用移动区域边界来提高总体内插质量。 视像相机让我们能够精确地确定移动区域; 因此,通过使用适当的损失功能强调这些地区,可以实现更好的视频框架内插质量。 结果显示测试数据集平均改善1.3美元dB, 以及主观上更令人满意的视觉结果,减少幽灵和模糊的文物。</s>
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