# Object Detection in Specific Traffic Scenes using YOLOv2

Source: [Object Detection in Specific Traffic Scenes using YOLOv2](<https://www.sota2.com/research/paper/68fa65bb1e209131cea0bf6a>)

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

Data updated: 2025-10-28T13:56:38.919Z

Authors: Shouyu Wang, Weitao Tang

Published: 2019-05-12T16:38:19.000Z

## Abstract

object detection framework plays crucial role in autonomous driving. In this paper, we introduce the real-time object detection framework called You Only Look Once (YOLOv1) and the related improvements of YOLOv2. We further explore the capability of YOLOv2 by implementing its pre-trained model to do the object detecting tasks in some specific traffic scenes. The four artificially designed traffic scenes include single-car, single-person, frontperson-rearcar and frontcar-rearperson.

## 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/1905.04740>)

[PDF](<https://arxiv.org/pdf/1905.04740.pdf>)