  In this report, we introduce our winning solution to the Real-time 3D
Detection and also the "Most Efficient Model" in the Waymo Open Dataset
Challenges at CVPR 2021. Extended from our last year's award-winning model
AFDet, we have made a handful of modifications to the base model, to improve
the accuracy and at the same time to greatly reduce the latency. The modified
model, named as AFDetV2, is featured with a lite 3D Feature Extractor, an
improved RPN with extended receptive field and an added sub-head that produces
an IoU-aware confidence score. These model enhancements, together with enriched
data augmentation, stochastic weights averaging, and a GPU-based implementation
of voxelization, lead to a winning accuracy of 73.12 mAPH/L2 for our AFDetV2
with a latency of 60.06 ms, and an accuracy of 72.57 mAPH/L2 for our
AFDetV2-base, entitled as the "Most Efficient Model" by the challenge sponsor,
with a winning latency of 55.86 ms.
