2nd Place Solution to ECCV 2020 VIPriors Object Detection Challenge

Autor: Gu, Yinzheng, Pan, Yihan, Chen, Shizhe
Rok vydání: 2020
Předmět:
Druh dokumentu: Working Paper
Popis: In this report, we descibe our approach to the ECCV 2020 VIPriors Object Detection Challenge which took place from March to July in 2020. We show that by using state-of-the-art data augmentation strategies, model designs, and post-processing ensemble methods, it is possible to overcome the difficulty of data shortage and obtain competitive results. Notably, our overall detection system achieves 36.6$\%$ AP on the COCO 2017 validation set using only 10K training images without any pre-training or transfer learning weights ranking us 2nd place in the challenge.
Comment: Technical report for the ECCV 2020 VIPriors Object Detection Challenge
Databáze: arXiv