Digital humanities research has flourished due to the diverse artifacts
...
Knowledge distillation (KD) exploits a large well-trained model (i.e.,
t...
This study introduces an efficacious approach, Masked Collaborative Cont...
A surge of interest has emerged in weakly supervised semantic segmentati...
Vision transformers have achieved remarkable success in computer vision ...
A surge of interest has emerged in utilizing Transformers in diverse vis...
The problem of deep long-tailed learning, a prevalent challenge in the r...
Despite the remarkable progress in semantic segmentation tasks with the
...
Recent proposed DETR variants have made tremendous progress in various
s...
Recently, long-tailed image classification harvests lots of research
att...
Recently, inspired by DETR variants, query-based end-to-end instance
seg...
In the realm of multi-modality, text-guided image retouching techniques
...
Semantic segmentation based on sparse annotation has advanced in recent
...
Significant progress has been made in learning image classification neur...
Deep transfer learning has been widely used for knowledge transmission i...
Neural networks (NNs) and decision trees (DTs) are both popular models o...
Most existing methods that cope with noisy labels usually assume that th...
Prototypical part network (ProtoPNet) has drawn wide attention and boost...
Both visual and auditory information are valuable to determine the salie...
Weakly supervised object localization is a challenging task which aims t...
Part-level attribute parsing is a fundamental but challenging task, whic...
Convolutional Neural Network (CNN), which mimics human visual perception...
Current weakly supervised semantic segmentation (WSSS) frameworks usuall...
Given a reference object of an unknown type in an image, human observers...
The microvascular invasion (MVI) is a major prognostic factor in
hepatoc...
When confronted with objects of unknown types in an image, humans can
ef...
We introduce a new network structure for decomposing an image into its
i...