VIPriors Object Detection Challenge

2020/07/16 by Zhipeng Luo, Luo, Zhipeng, Lixuan Che +1
Computer Science · Engineering · #Advanced Neural Network Applications #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Robotics and Sensor-Based Localization

paper · pdf · doi:10.48550/arxiv.2007.08170

openalex publication_date 2020/07/16 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

This paper is a brief report to our submission to the VIPriors Object Detection Challenge. Object Detection has attracted many researchers' attention for its full application, but it is still a challenging task. In this paper, we study analysis the characteristics of the data, and an effective data enhancement method is proposed. We carefully choose the model which is more suitable for training from scratch. We benefit a lot from using softnms and model fusion skillfully.

Citations

• DetectoRS: Detecting Objects with Recursive Feature Pyramid and Switchable Atrous Convolution

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