9.2k citations · 16.2k across the 175 of their papers we have counts for
19 papers · 1 filter
Learning Symmetry Consistent Deep CNNs for Face Completion
Xiaoming Li, Ming Liu, Jieru Zhu +4
Deep convolutional networks (CNNs) have achieved great success in face completion to generate plausible facial structures. These methods, however, are limited in maintaining global…
Model Inconsistent but Correlated Noise: Multi-view Subspace Learning with Regularized Mixture of Gaussians
Hongwei Yong, Deyu Meng, Jinxing Li +2
Multi-view subspace learning (MSL) aims to find a low-dimensional subspace of the data obtained from multiple views. Different from single view case, MSL should take both common an…
Convolutional Neural Networks based Intra Prediction for HEVC
Wenxue Cui, Tao Zhang, Shengping Zhang +3
Traditional intra prediction methods for HEVC rely on using the nearest reference lines for predicting a block, which ignore much richer context between the current block and its n…
Unsupervised/Semi-supervised Deep Learning for Low-dose CT Enhancement
Mingrui Geng, Yun Deng, Qian Zhao +4
Recently, deep learning(DL) methods have been proposed for the low-dose computed tomography(LdCT) enhancement, and obtain good trade-off between computational efficiency and image…
Joint Representation and Truncated Inference Learning for Correlation Filter based Tracking
Yingjie Yao, Xiaohe Wu, Lei Zhang +2
Correlation filter (CF) based trackers generally include two modules, i.e., feature representation and on-line model adaptation. In existing off-line deep learning models for CF tr…
Identity Preserving Face Completion for Large Ocular Region Occlusion
Yajie Zhao, Weikai Chen, Jun Xing +5
We present a novel deep learning approach to synthesize complete face images in the presence of large ocular region occlusions. This is motivated by recent surge of VR/AR displays…
Toward Convolutional Blind Denoising of Real Photographs
Shi Guo, Zifei Yan, Kai Zhang +2
While deep convolutional neural networks (CNNs) have achieved impressive success in image denoising with additive white Gaussian noise (AWGN), their performance remains limited on…
Multi-level Wavelet-CNN for Image Restoration
Pengju Liu, Hongzhi Zhang, Kai Zhang +2
The tradeoff between receptive field size and efficiency is a crucial issue in low level vision. Plain convolutional networks (CNNs) generally enlarge the receptive field at the ex…
PM-GANs: Discriminative Representation Learning for Action Recognition Using Partial-modalities
Lan Wang, Chenqiang Gao, Luyu Yang +3
Data of different modalities generally convey complimentary but heterogeneous information, and a more discriminative representation is often preferred by combining multiple data mo…
Learning Warped Guidance for Blind Face Restoration
Xiaoming Li, Ming Liu, Yuting Ye +3
This paper studies the problem of blind face restoration from an unconstrained blurry, noisy, low-resolution, or compressed image (i.e., degraded observation). For better recovery…
VITAL: VIsual Tracking via Adversarial Learning
Yibing Song, Chao Ma, Xiaohe Wu +6
The tracking-by-detection framework consists of two stages, i.e., drawing samples around the target object in the first stage and classifying each sample as the target object or as…
Multi-views Fusion CNN for Left Ventricular Volumes Estimation on Cardiac MR Images
Gongning Luo, Suyu Dong, Kuanquan Wang +3
Left ventricular (LV) volumes estimation is a critical procedure for cardiac disease diagnosis. The objective of this paper is to address direct LV volumes prediction task. Methods…
Multi-scale Location-aware Kernel Representation for Object Detection
Hao Wang, Qilong Wang, Mingqi Gao +2
Although Faster R-CNN and its variants have shown promising performance in object detection, they only exploit simple first-order representation of object proposals for final class…
Simultaneous Fidelity and Regularization Learning for Image Restoration
Dongwei Ren, Wangmeng Zuo, David Zhang +2
Most existing non-blind restoration methods are based on the assumption that a precise degradation model is known. As the degradation process can only be partially known or inaccur…
Metric Learning with Dynamically Generated Pairwise Constraints for Ear Recognition
Ibrahim Omara, Hongzhi Zhang, Faqiang Wang +1
Ear recognition task is known as predicting whether two ear images belong to the same person or not. In this paper, we present a novel metric learning method for ear recognition. T…
Learning Spatial-Temporal Regularized Correlation Filters for Visual Tracking
Feng Li, Cheng Tian, Wangmeng Zuo +2
Discriminative Correlation Filters (DCF) are efficient in visual tracking but suffer from unwanted boundary effects. Spatially Regularized DCF (SRDCF) has been suggested to resolve…
Deep Cocktail Network: Multi-source Unsupervised Domain Adaptation with Category Shift
Ruijia Xu, Ziliang Chen, Wangmeng Zuo +2
Unsupervised domain adaptation (UDA) conventionally assumes labeled source samples coming from a single underlying source distribution. Whereas in practical scenario, labeled data…
Shift-Net: Image Inpainting via Deep Feature Rearrangement
Zhaoyi Yan, Xiaoming Li, Mu Li +2
Deep convolutional networks (CNNs) have exhibited their potential in image inpainting for producing plausible results. However, in most existing methods, e.g., context encoder, the…
Enlarging Context with Low Cost: Efficient Arithmetic Coding with Trimmed Convolution
Mu Li, Shuhang Gu, David Zhang +1
Arithmetic coding is an essential class of coding techniques. One key issue of arithmetic encoding method is to predict the probability of the current coding symbol from its contex…