Pith. sign in

REVIEW

2nd Place Solution for Waymo Open Dataset Challenge -- 2D Object Detection

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2006.15507 v1 pith:3I2IBE36 submitted 2020-06-28 cs.CV

classification cs.CV
keywords detectiondatasetopensystemwaymoautonomousdetectordriving
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

A practical autonomous driving system urges the need to reliably and accurately detect vehicles and persons. In this report, we introduce a state-of-the-art 2D object detection system for autonomous driving scenarios. Specifically, we integrate both popular two-stage detector and one-stage detector with anchor free fashion to yield a robust detection. Furthermore, we train multiple expert models and design a greedy version of the auto ensemble scheme that automatically merges detections from different models. Notably, our overall detection system achieves 70.28 L2 mAP on the Waymo Open Dataset v1.2, ranking the 2nd place in the 2D detection track of the Waymo Open Dataset Challenges.

Discussion (0). Continue with ORCID to comment.

Pith tools