85 citations · 107 across the 4 of their papers we have counts for
5 papers · 1 filter
Uncertainty-aware Contrastive Distillation for Incremental Semantic Segmentation
Guanglei Yang, Enrico Fini, Dan Xu +5
A fundamental and challenging problem in deep learning is catastrophic forgetting, i.e. the tendency of neural networks to fail to preserve the knowledge acquired from old tasks wh…
Continual Attentive Fusion for Incremental Learning in Semantic Segmentation
Guanglei Yang, Enrico Fini, Dan Xu +5
Over the past years, semantic segmentation, as many other tasks in computer vision, benefited from the progress in deep neural networks, resulting in significantly improved perform…
Transformer-Based Source-Free Domain Adaptation
Guanglei Yang, Hao Tang, Zhun Zhong +4
In this paper, we study the task of source-free domain adaptation (SFDA), where the source data are not available during target adaptation. Previous works on SFDA mainly focus on a…
Transformer-Based Attention Networks for Continuous Pixel-Wise Prediction
Guanglei Yang, Hao Tang, Mingli Ding +2
While convolutional neural networks have shown a tremendous impact on various computer vision tasks, they generally demonstrate limitations in explicitly modeling long-range depend…
Bi-Directional Generation for Unsupervised Domain Adaptation
Guanglei Yang, Haifeng Xia, Mingli Ding +1
Unsupervised domain adaptation facilitates the unlabeled target domain relying on well-established source domain information. The conventional methods forcefully reducing the domai…