Event-based vision Sensors (EVS) utilize smart pixels capable of detecting whether relative illumination changes exceed a predefined temporal contrast threshold on a pixel level. As EVS asynchronously read these events, they provide low-latency and high-temporal resolution suitable for complementing conventional CMOS Image Sensors (CIS). Emerging hybrid CIS+EVS sensors fuse the high spatial resolution intensity frames with low latency event information to enhance applications such as deblur or video-frame interpolation (VFI) for slow-motion video capture. This paper employs an edge sharpness-based metric-Blurred Edge Width (BEW) to benchmark EVS-assisted slow-motion capture against CIS-only solutions. The EVS-assisted VFI interpolates a CIS video steam with a framerate of 120 fps by 64x, yielding an interpolated framerate of 7680 fps. We observed that the added information from EVS dramatically outperforms a 120 fps CIS-only VFI solution. Furthermore, the hybrid EVS+CIS-based VFI achieves comparable performance as high-speed CIS-only solutions that capture frames directly at 480 fps or 1920 fps and incorporate additional CIS-only VFI. These, however, do so at significantly lower data rates. In our study, factors 2.6 and 10.5 were observed.