IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Jan 19, 2022
The task of video moment retrieval (VMR) is to retrieve the specific video moment from an untrimmed video, according to a textual query. It is a challenging task that requires effective modeling of complex cross-modal matching relationship. Recent ef...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Jan 19, 2022
Survival prediction for patients based on histopa- thological whole-slide images (WSIs) has attracted increasing attention in recent years. Due to the massive pixel data in a single WSI, fully exploiting cell-level structural information (e.g., strom...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Jan 19, 2022
The success of deep convolutional networks (ConvNets) generally relies on a massive amount of well-labeled data, which is labor-intensive and time-consuming to collect and annotate in many scenarios. To eliminate such limitation, self-supervised lear...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Jan 12, 2022
Training deep models for RGB-D salient object detection (SOD) often requires a large number of labeled RGB-D images. However, RGB-D data is not easily acquired, which limits the development of RGB-D SOD techniques. To alleviate this issue, we present...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Jan 12, 2022
With the increasing popularity of convolutional neural networks (CNNs), recent works on face-based age estimation employ these networks as the backbone. However, state-of-the-art CNN-based methods treat each facial region equally, thus entirely ignor...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Jan 4, 2022
The deep unfolding network (DUN) provides an efficient framework for image restoration. It consists of a regularization module and a data fitting module. In existing DUN models, it is common to directly use a deep convolution neural network (DCNN) as...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Jan 4, 2022
Multi-modal retinal image registration plays an important role in the ophthalmological diagnosis process. The conventional methods lack robustness in aligning multi-modal images of various imaging qualities. Deep-learning methods have not been widely...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Dec 9, 2021
Along with the outstanding performance of the deep neural networks (DNNs), considerable research efforts have been devoted to finding ways to understand the decision of DNNs structures. In the computer vision domain, visualizing the attribution map i...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Nov 12, 2021
Spatial redundancy commonly exists in the learned representations of convolutional neural networks (CNNs), leading to unnecessary computation on high-resolution features. In this paper, we propose a novel Spatially Adaptive feature Refinement (SAR) a...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Oct 29, 2021
Adversarial images are imperceptible perturbations to mislead deep neural networks (DNNs), which have attracted great attention in recent years. Although several defense strategies achieved encouraging robustness against adversarial samples, most of ...