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1st solution for the Webly-supervised Fine-grained Recognition competition in https://www.cvmart.net/race/10412/base

Python 95.22% Shell 4.20% Dockerfile 0.58%

arcface-loss eql fine-grained-classification longtail mae pseudolabelling pytorch swin

accv2022_fgia_1st's Introduction

wangjinghuacom

流程中的自蒸馏的代码在哪儿，是指使用伪标签训练么？

请问这次比赛的数据集还有其他下载途径吗？官网只能报名才能下载数据集，但报名时间早已经过去了。

@Ezra-Yu 非常感谢您的工作。当前有些疑问，麻烦解惑~

目的：MAE预训练的资源和成本过高，想了解收益如何？
问题：MAE是否有消融实验结果？如果没有，MAE-ViT在比赛过程中的提升过程也OK~

再次感谢，期待回复~

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