30 citations · 57 across the 11 of their papers we have counts for
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cs.CV2021★ 8 cited
Sharpness-aware Quantization for Deep Neural Networks
Jing Liu, Jianfei Cai, Bohan Zhuang
Network quantization is a dominant paradigm of model compression. However, the abrupt changes in quantized weights during training often lead to severe loss fluctuations and result…
cs.CV2021★ 4 cited
Mesa: A Memory-saving Training Framework for Transformers
Zizheng Pan, Peng Chen, Haoyu He +3
There has been an explosion of interest in designing high-performance Transformers. While Transformers have delivered significant performance improvements, training such networks i…
cs.CV2021
Mutual Consistency Learning for Semi-supervised Medical Image Segmentation
Yicheng Wu, Zongyuan Ge, Donghao Zhang +4
In this paper, we propose a novel mutual consistency network (MC-Net+) to effectively exploit the unlabeled data for semi-supervised medical image segmentation. The MC-Net+ model i…