21 citations · 68 across the 17 of their papers we have counts for
18 papers
Heterogeneous Forgetting Compensation for Class-Incremental Learning
Jiahua Dong, Wenqi Liang, Yang Cong +1
Class-incremental learning (CIL) has achieved remarkable successes in learning new classes consecutively while overcoming catastrophic forgetting on old categories. However, most e…
Self-paced Weight Consolidation for Continual Learning
Wei Cong, Yang Cong, Gan Sun +2
Continual learning algorithms which keep the parameters of new tasks close to that of previous tasks, are popular in preventing catastrophic forgetting in sequential task learning…
Gradient-Semantic Compensation for Incremental Semantic Segmentation
Wei Cong, Yang Cong, Jiahua Dong +2
Incremental semantic segmentation aims to continually learn the segmentation of new coming classes without accessing the training data of previously learned classes. However, most…
InOR-Net: Incremental 3D Object Recognition Network for Point Cloud Representation
Jiahua Dong, Yang Cong, Gan Sun +4
3D object recognition has successfully become an appealing research topic in the real-world. However, most existing recognition models unreasonably assume that the categories of 3D…
No One Left Behind: Real-World Federated Class-Incremental Learning
Jiahua Dong, Hongliu Li, Yang Cong +3
Federated learning (FL) is a hot collaborative training framework via aggregating model parameters of decentralized local clients. However, most FL methods unreasonably assume data…
Unsupervised Dense Deformation Embedding Network for Template-Free Shape Correspondence
Ronghan Chen, Yang Cong, Jiahua Dong
Shape correspondence from 3D deformation learning has attracted appealing academy interests recently. Nevertheless, current deep learning based methods require the supervision of d…