IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Jun 9, 2022
Image hazing aims to render a hazy image from a given clean one, which could be applied to a variety of practical applications such as gaming, filming, photographic filtering, and image dehazing. To generate plausible haze, we study two less-touched ...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Jun 9, 2022
Most video-based person re-identification (re-id) methods only focus on appearance features but neglect motion features. In fact, motion features can help to distinguish the target persons that are hard to be identified only by appearance features. H...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Apr 11, 2022
In this paper, a Multi-scale Contrastive Graph Convolutional Network (MC-GCN) method is proposed for unconstrained face recognition with image sets, which takes a set of media (orderless images and videos) as a face subject instead of single media (a...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Apr 11, 2022
Deep feature embedding aims to learn discriminative features or feature embeddings for image samples which can minimize their intra-class distance while maximizing their inter-class distance. Recent state-of-the-art methods have been focusing on lear...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Apr 8, 2022
Deep neural networks have achieved remarkable progress in single-image 3D human reconstruction. However, existing methods still fall short in predicting rare poses. The reason is that most of the current models perform regression based on a single hu...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Apr 4, 2022
Unsupervised active learning has become an active research topic in the machine learning and computer vision communities, whose goal is to choose a subset of representative samples to be labeled in an unsupervised setting. Most of existing approaches...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Mar 31, 2022
Sketch recognition relies on two types of information, namely, spatial contexts like the local structures in images and temporal contexts like the orders of strokes. Existing methods usually adopt convolutional neural networks (CNNs) to model spatial...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Mar 22, 2022
In recent years, the community of object detection has witnessed remarkable progress with the development of deep neural networks. But the detection performance still suffers from the dilemma between complex networks and single-vector predictions. In...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Mar 21, 2022
The explanation for deep neural networks has drawn extensive attention in the deep learning community over the past few years. In this work, we study the visual saliency, a.k.a. visual explanation, to interpret convolutional neural networks. Compared...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Mar 15, 2022
Image inpainting has made remarkable progress with recent advances in deep learning. Popular networks mainly follow an encoder-decoder architecture (sometimes with skip connections) and possess sufficiently large receptive field, i.e., larger than th...