BlazeBVD: Make Scale-Time Equalization Great Again for Blind Video Deflickering

arXiv:2403.06243v1 Announce Type: new
Abstract: Developing blind video deflickering (BVD) algorithms to enhance video temporal consistency, is gaining importance amid the flourish of image processing and video generation. However, the intricate nature of video data complicates the training of deep learning methods, leading to high resource consumption and instability, notably under severe lighting flicker. This underscores the critical need for a compact representation beyond pixel values to advance BVD research and applications. Inspired by the classic scale-time equalization (STE), our …

abstract algorithms arxiv blind consumption cs.cv data deep learning equalization flourish however image image processing importance nature processing scale temporal training type video video data video generation