# PFDet: 2nd Place Solution to Open Images Challenge 2018 Object Detection Track

Source: [PFDet: 2nd Place Solution to Open Images Challenge 2018 Object Detection Track](<https://www.sota2.com/research/paper/68fa64c81e209131cea0691e>)

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

Data updated: 2025-10-25T21:11:58.696Z

Authors: Takuya Akiba, Tommi Kerola, Yusuke Niitani, Toru Ogawa, Shotaro Sano, Shuji Suzuki

Published: 2018-09-04T02:59:07.000Z

## Abstract

We present a large-scale object detection system by team PFDet. Our system enables training with huge datasets using 512 GPUs, handles sparsely verified classes, and massive class imbalance. Using our method, we achieved 2nd place in the Google AI Open Images Object Detection Track 2018 on Kaggle.

## 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/1809.00778>)

[PDF](<https://arxiv.org/pdf/1809.00778.pdf>)