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：利用事件相机有望提升视频帧插值方案的视觉质量。我们提出了一种基于学习的方法，通过挖掘视频序列中的运动区域边界来提高整体插值质量。事件相机能够精确地确定运动区域，因此通过使用合适的损失函数强调这些区域，可以实现更好的视频帧插值质量。结果表明，在测试数据集上平均峰值信噪比（PSNR）提升了1.3 dB，同时主观上获得了更令人满意的视觉结果，重影和模糊伪影更少。