192 citations · 789 across the 43 of their papers we have counts for
9 papers · 1 filter
Exploring Robustness of Unsupervised Domain Adaptation in Semantic Segmentation
Jinyu Yang, Chunyuan Li, Weizhi An +5
Recent studies imply that deep neural networks are vulnerable to adversarial examples -- inputs with a slight but intentional perturbation are incorrectly classified by the network…
Towards Accurate and Compact Architectures via Neural Architecture Transformer
Yong Guo, Yin Zheng, Mingkui Tan +5
Designing effective architectures is one of the key factors behind the success of deep neural networks. Existing deep architectures are either manually designed or automatically se…
Breaking the Curse of Space Explosion: Towards Efficient NAS with Curriculum Search
Yong Guo, Yaofo Chen, Yin Zheng +4
Neural architecture search (NAS) has become an important approach to automatically find effective architectures. To cover all possible good architectures, we need to search in an e…
Collaborative Unsupervised Domain Adaptation for Medical Image Diagnosis
Yifan Zhang, Ying Wei, Qingyao Wu +4
Deep learning based medical image diagnosis has shown great potential in clinical medicine. However, it often suffers two major difficulties in real-world applications: 1) only lim…
Disturbance-immune Weight Sharing for Neural Architecture Search
Shuaicheng Niu, Jiaxiang Wu, Yifan Zhang +4
Neural architecture search (NAS) has gained increasing attention in the community of architecture design. One of the key factors behind the success lies in the training efficiency…
Context-Aware Domain Adaptation in Semantic Segmentation
Jinyu Yang, Weizhi An, Chaochao Yan +2
In this paper, we consider the problem of unsupervised domain adaptation in the semantic segmentation. There are two primary issues in this field, i.e., what and how to transfer do…