Large-scale well-annotated datasets are of great importance for training...
Weak feature representation problem has influenced the performance of
fe...
Recently, density map regression-based methods have dominated in crowd
c...
Few-shot learning problem focuses on recognizing unseen classes given a ...
Few-Shot Learning (FSL) alleviates the data shortage challenge via embed...
Change detection (CD) aims to identify changes that occur in an image pa...
Few-shot semantic segmentation aims to segment novel-class objects in a ...
Boundary-based instance segmentation has drawn much attention since of i...
Few-shot semantic segmentation aims to segment novel-class objects in a ...
Facial attributes (e.g., age and attractiveness) estimation performance ...
Multi-label image recognition is a practical and challenging task compar...
Object detection aims at high speed and accuracy simultaneously. However...
The difficulty of image recognition has gradually increased from general...
Convolutional Neural Networks (ConvNets) have achieved excellent recogni...
Convolutional neural networks (CNNs) have shown great performance as gen...
In this paper we show that by carefully making good choices for various
...
In computer vision, an entity such as an image or video is often represe...