204 citations · 388 across the 43 of their papers we have counts for
4 papers · 1 filter
Learning Disentangled Representation for One-shot Progressive Face Swapping
Qi Li, Weining Wang, Chengzhong Xu +2
Although face swapping has attracted much attention in recent years, it remains a challenging problem. Existing methods leverage a large number of data samples to explore the intri…
Towards Inadequately Pre-trained Models in Transfer Learning
Andong Deng, Xingjian Li, Di Hu +3
Pre-training has been a popular learning paradigm in deep learning era, especially in annotation-insufficient scenario. Better ImageNet pre-trained models have been demonstrated, f…
Adaptive Consistency Regularization for Semi-Supervised Transfer Learning
Abulikemu Abuduweili, Xingjian Li, Humphrey Shi +2
While recent studies on semi-supervised learning have shown remarkable progress in leveraging both labeled and unlabeled data, most of them presume a basic setting of the model is…
Dynamic Channel Pruning: Feature Boosting and Suppression
Xitong Gao, Yiren Zhao, Łukasz Dudziak +2
Making deep convolutional neural networks more accurate typically comes at the cost of increased computational and memory resources. In this paper, we reduce this cost by exploitin…