SEMI-PointRend: Improved Semiconductor Wafer Defect Classification and Segmentation as Rendering

In this study, we applied the PointRend (Point-based Rendering) method to semiconductor defect segmentation. PointRend is an iterative segmentation algorithm inspired by image rendering in computer graphics, a new image segmentation method that can generate high-resolution segmentation masks. It can also be flexibly integrated into common instance segmentation meta-architecture such as Mask-RCNN and semantic meta-architecture such as FCN. We implemented a model, termed as SEMI-<PRE_TAG>PointRend</POST_TAG>, to generate precise segmentation masks by applying the PointRend neural network module. In this paper, we focus on comparing the defect segmentation predictions of SEMI-<PRE_TAG>PointRend</POST_TAG> and Mask-RCNN for various defect types (line-collapse, single bridge, thin bridge, multi bridge non-horizontal). We show that SEMI-<PRE_TAG>PointRend</POST_TAG> can outperforms Mask R-CNN by up to 18.8% in terms of segmentation mean average precision.