# 1st Place Solutions of Waymo Open Dataset Challenge 2020 -- 2D Object Detection Track

Source: [1st Place Solutions of Waymo Open Dataset Challenge 2020 -- 2D Object Detection Track](<https://www.sota2.com/research/paper/68fa68181e209131cea1a2b2>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-25T22:29:00.055Z

Authors: Zehao Huang, Zehui Chen, Qiaofei Li, Hongkai Zhang, Naiyan Wang

Published: 2020-08-04T06:46:28.000Z

## Abstract

In this technical report, we present our solutions of Waymo Open Dataset (WOD) Challenge 2020 - 2D Object Track. We adopt FPN as our basic framework. Cascade RCNN, stacked PAFPN Neck and Double-Head are used for performance improvements. In order to handle the small object detection problem in WOD, we use very large image scales for both training and testing. Using our methods, our team RW-TSDet achieved the 1st place in the 2D Object Detection Track.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2008.01365>)

[PDF](<https://arxiv.org/pdf/2008.01365.pdf>)