32 citations · 114 across the 17 of their papers we have counts for
17 papers
Filter Pruning for Efficient CNNs via Knowledge-driven Differential Filter Sampler
Shaohui Lin, Wenxuan Huang, Jiao Xie +5
Filter pruning simultaneously accelerates the computation and reduces the memory overhead of CNNs, which can be effectively applied to edge devices and cloud services. In this pape…
AttriCLIP: A Non-Incremental Learner for Incremental Knowledge Learning
Runqi Wang, Xiaoyue Duan, Guoliang Kang +5
Continual learning aims to enable a model to incrementally learn knowledge from sequentially arrived data. Previous works adopt the conventional classification architecture, which…
DCS-RISR: Dynamic Channel Splitting for Efficient Real-world Image Super-Resolution
Junbo Qiao, Shaohui Lin, Yunlun Zhang +5
Real-world image super-resolution (RISR) has received increased focus for improving the quality of SR images under unknown complex degradation. Existing methods rely on the heavy S…
MISSU: 3D Medical Image Segmentation via Self-distilling TransUNet
Nan Wang, Shaohui Lin, Xiaoxiao Li +4
U-Nets have achieved tremendous success in medical image segmentation. Nevertheless, it may suffer limitations in global (long-range) contextual interactions and edge-detail preser…
A Closer Look at Branch Classifiers of Multi-exit Architectures
Shaohui Lin, Bo Ji, Rongrong Ji +1
Multi-exit architectures consist of a backbone and branch classifiers that offer shortened inference pathways to reduce the run-time of deep neural networks. In this paper, we anal…
Novelty Detection via Contrastive Learning with Negative Data Augmentation
Chengwei Chen, Yuan Xie, Shaohui Lin +5
Novelty detection is the process of determining whether a query example differs from the learned training distribution. Previous methods attempt to learn the representation of the…