4 citations · 15 across the 12 of their papers we have counts for
4 papers · 1 filter
DTL: Disentangled Transfer Learning for Visual Recognition
Minghao Fu, Ke Zhu, Jianxin Wu
When pre-trained models become rapidly larger, the cost of fine-tuning on downstream tasks steadily increases, too. To economically fine-tune these models, parameter-efficient tran…
Multi-Label Self-Supervised Learning with Scene Images
Ke Zhu, Minghao Fu, Jianxin Wu
Self-supervised learning (SSL) methods targeting scene images have seen a rapid growth recently, and they mostly rely on either a dedicated dense matching mechanism or a costly uns…
ESTISR: Adapting Efficient Scene Text Image Super-resolution for Real-Scenes
Minghao Fu, Xin Man, Yihan Xu +1
While scene text image super-resolution (STISR) has yielded remarkable improvements in accurately recognizing scene text, prior methodologies have placed excessive emphasis on opti…
Instance-based Max-margin for Practical Few-shot Recognition
Minghao Fu, Ke Zhu, Jianxin Wu
In order to mimic the human few-shot learning (FSL) ability better and to make FSL closer to real-world applications, this paper proposes a practical FSL (pFSL) setting. pFSL is ba…