3 citations · 6 across the 7 of their papers we have counts for
5 papers · 1 filter
Two-level Graph Network for Few-Shot Class-Incremental Learning
Hao Chen, Linyan Li, Fan Lyu +3
Few-shot class-incremental learning (FSCIL) aims to design machine learning algorithms that can continually learn new concepts from a few data points, without forgetting knowledge…
Multi-Label Continual Learning using Augmented Graph Convolutional Network
Kaile Du, Fan Lyu, Linyan Li +5
Multi-Label Continual Learning (MLCL) builds a class-incremental framework in a sequential multi-label image recognition data stream. The critical challenges of MLCL are the constr…
AGCN: Augmented Graph Convolutional Network for Lifelong Multi-label Image Recognition
Kaile Du, Fan Lyu, Fuyuan Hu +4
The Lifelong Multi-Label (LML) image recognition builds an online class-incremental classifier in a sequential multi-label image recognition data stream. The key challenges of LML…
Each Attribute Matters: Contrastive Attention for Sentence-based Image Editing
Liuqing Zhao, Fan Lyu, Fuyuan Hu +3
Sentence-based Image Editing (SIE) aims to deploy natural language to edit an image. Offering potentials to reduce expensive manual editing, SIE has attracted much interest recentl…
Exploiting Color Name Space for Salient Object Detection
Jing Lou, Huan Wang, Longtao Chen +4
In this paper, we will investigate the contribution of color names for the task of salient object detection. An input image is first converted to color name space, which is consist…