This is a very short technical report, which introduces the solution of the Team BUPT-CASIA for Short-video Face Parsing Track of The 3rd Person in Context (PIC) Workshop and Challenge at CVPR 2021. Face parsing has recently attracted increasing interest due to its numerous application potentials. Generally speaking, it has a lot in common with human parsing, such as task setting, data characteristics, number of categories and so on. Therefore, this work applies state-of-the-art human parsing method to face parsing task to explore the similarities and differences between them. Our submission achieves 86.84% score and wins the 2nd place in the challenge.
翻译:这是一份非常简短的技术报告,其中介绍了BUPT-CASIA小组的解决方案,用于对第三人背景的短视视剖面跟踪(PIC)讲习班和CVPR 2021 挑战。面面面分析最近由于应用潜力众多而引起越来越多的兴趣。一般而言,它与人类划分有许多共同之处,例如任务设置、数据特征、类别数目等等。因此,这项工作采用最先进的人类分解方法来应对分析任务,以探究它们之间的异同。我们的呈文达到了86.84%的得分,赢得了挑战中的第2位。