  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.
