Text-to-image generative models can produce diverse high-quality images ...
Class-incremental learning (CIL) has achieved remarkable successes in
le...
Continual learning algorithms which keep the parameters of new tasks clo...
Incremental semantic segmentation aims to continually learn the segmenta...
Federated learning-based semantic segmentation (FSS) has drawn widesprea...
3D object recognition has successfully become an appealing research topi...
Federated learning (FL) is a hot collaborative training framework via
ag...
Rotation-invariant (RI) 3D deep learning methods suffer performance
degr...
Shape correspondence from 3D deformation learning has attracted appealin...
3D object classification has attracted appealing attentions in academic
...
Weakly-supervised learning has attracted growing research attention on
m...
Unsupervised domain adaptation without consuming annotation process for
...
Online metric learning has been widely exploited for large-scale data
cl...
Unsupervised domain adaptation has attracted growing research attention ...
Federated machine learning which enables resource constrained node devic...
The 3D mesh is an important representation of geometric data. In the
gen...
We propose a single-shot method for simultaneous 3D object segmentation ...
3D object recognition has been widely-applied. However, most
state-of-th...
In the past decades, spectral clustering (SC) has become one of the most...
Object clustering, aiming at grouping similar objects into one cluster w...
Weakly-supervised learning under image-level labels supervision has been...
Consider the lifelong learning paradigm whose objective is to learn a
se...
The state-of-the-art online learning approaches are only capable of lear...