论文标题
强大的视觉挑战2020-综合分段的第一名报告
Robust Vision Challenge 2020 -- 1st Place Report for Panoptic Segmentation
论文作者
论文摘要
在此技术报告中，我们介绍了获胜的全盘细分体系结构fefps_b1bs4_rvc的关键细节。我们的网络是我们最先进的有效体系结构的轻量级版本，它由我们提出的共享主链组成，并用修改后的Extricnet-B5模型作为编码器，然后是2-Way FPN，以学习语义上丰富的多尺度功能。它由两个特定于任务的头部，一个修改的蒙版R-CNN实例头和我们的新型语义分割头组成，它们与专门的模块一起处理不同尺度的特征，以进行连贯的特征细化。最后，我们提出的全景融合模块可适应从每个头部的逻辑融合，以产生泛型分割输出。强大的视觉挑战2020基准测试结果表明，我们的模型在Microsoft Coco，Viper和Wilddash上排名第一，在CityScapes和Mapillary Vistas上排名第二，从而获得了全盘细分任务的总排名第一。
In this technical report, we present key details of our winning panoptic segmentation architecture EffPS_b1bs4_RVC. Our network is a lightweight version of our state-of-the-art EfficientPS architecture that consists of our proposed shared backbone with a modified EfficientNet-B5 model as the encoder, followed by the 2-way FPN to learn semantically rich multi-scale features. It consists of two task-specific heads, a modified Mask R-CNN instance head and our novel semantic segmentation head that processes features of different scales with specialized modules for coherent feature refinement. Finally, our proposed panoptic fusion module adaptively fuses logits from each of the heads to yield the panoptic segmentation output. The Robust Vision Challenge 2020 benchmarking results show that our model is ranked #1 on Microsoft COCO, VIPER and WildDash, and is ranked #2 on Cityscapes and Mapillary Vistas, thereby achieving the overall rank #1 for the panoptic segmentation task.
