21 citations · 68 across the 17 of their papers we have counts for
8 papers · 1 filter
I3DOL: Incremental 3D Object Learning without Catastrophic Forgetting
Jiahua Dong, Yang Cong, Gan Sun +2
3D object classification has attracted appealing attentions in academic researches and industrial applications. However, most existing methods need to access the training data of p…
Weakly-Supervised Cross-Domain Adaptation for Endoscopic Lesions Segmentation
Jiahua Dong, Yang Cong, Gan Sun +3
Weakly-supervised learning has attracted growing research attention on medical lesions segmentation due to significant saving in pixel-level annotation cost. However, 1) most exist…
Generative Partial Visual-Tactile Fused Object Clustering
Tao Zhang, Yang Cong, Gan Sun +3
Visual-tactile fused sensing for object clustering has achieved significant progresses recently, since the involvement of tactile modality can effectively improve clustering perfor…
CSCL: Critical Semantic-Consistent Learning for Unsupervised Domain Adaptation
Jiahua Dong, Yang Cong, Gan Sun +2
Unsupervised domain adaptation without consuming annotation process for unlabeled target data attracts appealing interests in semantic segmentation. However, 1) existing methods ne…
Evolving Metric Learning for Incremental and Decremental Features
Jiahua Dong, Yang Cong, Gan Sun +3
Online metric learning has been widely exploited for large-scale data classification due to the low computational cost. However, amongst online practical scenarios where the featur…
What Can Be Transferred: Unsupervised Domain Adaptation for Endoscopic Lesions Segmentation
Jiahua Dong, Yang Cong, Gan Sun +2
Unsupervised domain adaptation has attracted growing research attention on semantic segmentation. However, 1) most existing models cannot be directly applied into lesions transfer…