IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Mar 15, 2022
Numerous single image super-resolution (SISR) algorithms have been proposed during the past years to reconstruct a high-resolution (HR) image from its low-resolution (LR) observation. However, how to fairly compare the performance of different SISR a...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Mar 8, 2022
Recently, the siamese convolutional neural network plays an important role in the field of visual tracking, which can obtain high tracking accuracy and good real-time performance. However, the requirement of offline training a specific neural network...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Mar 8, 2022
When training samples are scarce, the semantic embedding technique, i. e., describing class labels with attributes, provides a condition to generate visual features for unseen objects by transferring the knowledge from seen objects. However, semantic...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Mar 2, 2022
Multi-source domain adaptation (MDA) aims to transfer knowledge from multiple source domains to an unlabeled target domain. MDA is a challenging task due to the severe domain shift, which not only exists between target and source but also exists amon...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Feb 16, 2022
Recently, many arbitrary-oriented object detection (AOOD) methods have been proposed and attracted widespread attention in many fields. However, most of them are based on anchor-boxes or standard Gaussian heatmaps. Such label assignment strategy may ...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Feb 16, 2022
OCT fluid segmentation is a crucial task for diagnosis and therapy in ophthalmology. The current convolutional neural networks (CNNs) supervised by pixel-wise annotated masks achieve great success in OCT fluid segmentation. However, requiring pixel-w...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Feb 1, 2022
Convolutional Neural Networks (CNN) and Graph Neural Networks (GNN), such as Graph Attention Networks (GAT), are two classic neural network models, which are applied to the processing of grid data and graph data respectively. They have achieved outst...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Feb 1, 2022
Unsupervised domain adaptation (UDA) for person re-identification is challenging because of the huge gap between the source and target domain. A typical self-training method is to use pseudo-labels generated by clustering algorithms to iteratively op...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Jan 28, 2022
Deep learning has enabled significant improvements in the accuracy of 3D blood vessel segmentation. Open challenges remain in scenarios where labeled 3D segmentation maps for training are severely limited, as is often the case in practice, and in ens...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Jan 25, 2022
Model fine-tuning is a widely used transfer learning approach in person Re-identification (ReID) applications, which fine-tuning a pre-trained feature extraction model into the target scenario instead of training a model from scratch. It is challengi...