IEEE transactions on pattern analysis and machine intelligence
Jun 30, 2023
Graph matching (GM) has been a long-standing combinatorial problem due to its NP-hard nature. Recently (deep) learning-based approaches have shown their superiority over the traditional solvers while the methods are almost based on supervised learnin...
IEEE transactions on pattern analysis and machine intelligence
Jun 30, 2023
Normalization techniques are essential for accelerating the training and improving the generalization of deep neural networks (DNNs), and have successfully been used in various applications. This paper reviews and comments on the past, present and fu...
IEEE transactions on pattern analysis and machine intelligence
Jun 30, 2023
Modern medical imaging techniques, such as ultrasound (US) and cardiac magnetic resonance (MR) imaging, have enabled the evaluation of myocardial deformation directly from an image sequence. While many traditional cardiac motion tracking methods have...
IEEE transactions on pattern analysis and machine intelligence
Jun 30, 2023
We present compact and effective deep convolutional neural networks (CNNs) by exploring properties of videos for video deblurring. Motivated by the non-uniform blur property that not all the pixels of the frames are blurry, we develop a CNN to integr...
IEEE transactions on pattern analysis and machine intelligence
Jun 30, 2023
Availability of labelled data is the major obstacle to the deployment of deep learning algorithms for computer vision tasks in new domains. The fact that many frameworks adopted to solve different tasks share the same architecture suggests that there...
IEEE transactions on pattern analysis and machine intelligence
Jun 30, 2023
Image restoration under adverse weather conditions has been of significant interest for various computer vision applications. Recent successful methods rely on the current progress in deep neural network architectural designs (e.g., with vision trans...
IEEE transactions on pattern analysis and machine intelligence
Jun 30, 2023
Deep learning for change detection is one of the current hot topics in the field of remote sensing. However, most end-to-end networks are proposed for supervised change detection, and unsupervised change detection models depend on traditional pre-det...
IEEE transactions on pattern analysis and machine intelligence
Jun 30, 2023
Visible and infrared image fusion (VIF) has attracted a lot of interest in recent years due to its application in many tasks, such as object detection, object tracking, scene segmentation, and crowd counting. In addition to conventional VIF methods, ...
IEEE transactions on pattern analysis and machine intelligence
Jun 30, 2023
The Area Under the ROC Curve (AUC) is a crucial metric for machine learning, which evaluates the average performance over all possible True Positive Rates (TPRs) and False Positive Rates (FPRs). Based on the knowledge that a skillful classifier shoul...
IEEE transactions on pattern analysis and machine intelligence
Jun 30, 2023
Previous works for LiDAR-based 3D object detection mainly focus on the single-frame paradigm. In this paper, we propose to detect 3D objects by exploiting temporal information in multiple frames, i.e., point cloud videos. We empirically categorize th...