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arXiv · 2006.10702

Semi-Supervised Recognition under a Noisy and Fine-grained Dataset

Cheng Cui·Zhi Ye·Yangxi Li·Xinjian Li·Min Yang·Kai Wei·Bing Dai·Yanmei Zhao·Zhongji Liu·Rong Pang
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Abstract

Simi-Supervised Recognition Challenge-FGVC7 is a challenging fine-grained recognition competition. One of the difficulties of this competition is how to use unlabeled data. We adopted pseudo-tag data mining to increase the amount of training data. The other one is how to identify similar birds with a very small difference, especially those have a relatively tiny main-body in examples. We combined generic image recognition and fine-grained image recognition method to solve the problem. All generic image recognition models were training using PaddleClas . Using the combination of two different ways of deep recognition models, we finally won the third place in the competition.

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Cheng Cui, Zhi Ye, Yangxi Li, Xinjian Li, Min Yang, Kai Wei, Bing Dai, Yanmei Zhao, Zhongji Liu, Rong Pang. 2020-06-18. Semi-Supervised Recognition under a Noisy and Fine-grained Dataset. https://arxiv.org/abs/2006.10702

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