Rethinking Video Error Concealment: A Benchmark Dataset

Error concealment is an important technique to restore a damaged video bistream. Although data-driven in-painting methods can be directly applied to video error concealment, existing mask patterns are remarkably different from the practical damaged video bitstream, which causes a great impact on the repairing effect of video quality. To rethink the gap between existing inpainting schemes and practical video transmission characteristics, we have established a new video error concealment (VEC) benchmark dataset. Specifically, different video sequences compressed by different encoders are collected, and various loss types are generated to satisfy different packet loss scenarios. Based on VEC, error-concealed results of existing methods are provided and analyzed, which can serve as a benchmark for video error concealment research.