Block permutation and Co-XOR (BPCX) image encryption is a commonly used encryption method for reversible data hiding in the encryption domain, which can effectively improve the embedded capacity and the ability resisting the existing attacks including …
Although massive pruning methods are emerging for achieving structural sparsity in convolutional neural networks (CNN), most of them target structures such as ResNet. Meanwhile, previous works take more interest in pruning filters inside a residual blo…
Modeling the moving behaviors and predicting the future paths of pedestrians, especially for those in complex scenes, remain a challenging problem in machine learning. We recognize that human motion trajectories, governed by social norms and constraine…
Multicast is a promising solution to address spectrum scarcity in wireless video streaming, while facing tough challenge in provisioning quality of service (QoS) to heterogeneous users. This article presents an adaptive modulation and coding (AMC) sche…
Subspace clustering has been extensively studied from the hypothesis-and-test, algebraic, and spectral clustering-based perspectives. Most assume that only a single type/class of subspace is present. Generalizations to multiple types are non-trivial, p…
Moving cast shadow identification and extraction are the commonly encountered problems in visual surveillance applications. In the video object detection problem, a shadow is a category of the dynamic entity which needs to be removed for accurate detec…
Prevailing deep methods for image recognition require massive labeled samples in each visual category for training. However, large amounts of data annotations are timeconsuming, and some uncommon categories only have rare samples available. For this is…
Keypoints matching is a pivotal component for many image-relevant applications such as image stitching, visual simultaneous localization and mapping (SLAM), and so on. Both handcrafted-based and recently emerged deep learning-based keypoints matching m…
Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.
In this letter, we propose a general digital image operation anti-forensic framework based on generative adversarial nets (GANs), called dual-domain generative adversarial network (DDGAN). To tackle the issue of image operation detection, the proposed …