32 citations · 114 across the 17 of their papers we have counts for
5 papers · 1 filter
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…
Towards Compact Single Image Super-Resolution via Contrastive Self-distillation
Yanbo Wang, Shaohui Lin, Yanyun Qu +4
Convolutional neural networks (CNNs) are highly successful for super-resolution (SR) but often require sophisticated architectures with heavy memory cost and computational overhead…
Towards Compact CNNs via Collaborative Compression
Yuchao Li, Shaohui Lin, Jianzhuang Liu +7
Channel pruning and tensor decomposition have received extensive attention in convolutional neural network compression. However, these two techniques are traditionally deployed in…
Contrastive Learning for Compact Single Image Dehazing
Haiyan Wu, Yanyun Qu, Shaohui Lin +5
Single image dehazing is a challenging ill-posed problem due to the severe information degeneration. However, existing deep learning based dehazing methods only adopt clear images…
Farewell to Mutual Information: Variational Distillation for Cross-Modal Person Re-Identification
Xudong Tian, Zhizhong Zhang, Shaohui Lin +3
The Information Bottleneck (IB) provides an information theoretic principle for representation learning, by retaining all information relevant for predicting label while minimizing…