no code implementations • 29 Sep 2021 • Mengbiao Zhao, Shixiong Xu, Jianlong Chang, Lingxi Xie, Jie Chen, Qi Tian
Having consumed huge amounts of training data and computational resource, large-scale pre-trained models are often considered key assets of AI service providers.
no code implementations • 1 Dec 2020 • Mengbiao Zhao, Wei Feng, Fei Yin, Xu-Yao Zhang, Cheng-Lin Liu
We propose an Expectation-Maximization (EM) based weakly-supervised learning framework to train an accurate arbitrary-shaped text detector using only a small amount of polygon-level annotated data combined with a large amount of weakly annotated data.