39 citations · 67 across the 3 of their papers we have counts for
3 papers
cs.CV2020★ 7 cited
Adversarial-Learned Loss for Domain Adaptation
Minghao Chen, Shuai Zhao, Haifeng Liu +1
Recently, remarkable progress has been made in learning transferable representation across domains. Previous works in domain adaptation are majorly based on two techniques: domain-…
cs.CV2019★ 21 cited
DBP: Discrimination Based Block-Level Pruning for Deep Model Acceleration
Wenxiao Wang, Shuai Zhao, Minghao Chen +3
Neural network pruning is one of the most popular methods of accelerating the inference of deep convolutional neural networks (CNNs). The dominant pruning methods, filter-level pru…
cs.CV2019★ 39 cited
Domain Adaptation for Semantic Segmentation with Maximum Squares Loss
Minghao Chen, Hongyang Xue, Deng Cai
Deep neural networks for semantic segmentation always require a large number of samples with pixel-level labels, which becomes the major difficulty in their real-world applications…