• Publications
  • Influence
Fast and Accurate Single Image Super-Resolution via Information Distillation Network
TLDR
We propose a deep but compact convolutional network to directly reconstruct the high resolution image from the original low resolution image. Expand
Ordinal Regression with Multiple Output CNN for Age Estimation
TLDR
We propose an End-to-End learning approach to address ordinal regression problems using deep Convolutional Neural Network, which could simultaneously conduct feature learning and regression modeling. Expand
A survey of graph edit distance
TLDR
Graph edit distance (GED) is the base of inexact graph matching. Expand
Single Image Super-Resolution With Non-Local Means and Steering Kernel Regression
TLDR
We propose a novel image SR method by learning both non-local and local regularization priors from a given low-resolution image. Expand
Self-Supervised Adversarial Hashing Networks for Cross-Modal Retrieval
TLDR
In this paper, we propose a self-supervised adversarial hashing (SSAH) approach, which lies among the early attempts to incorporate adversarial learning into cross-modal hashing in a self supervised fashion. Expand
Lightweight Image Super-Resolution with Information Multi-distillation Network
TLDR
In recent years, single image super-resolution (SISR) methods using deep convolution neural network (CNN) have achieved impressive results. Expand
Blind Image Quality Assessment via Deep Learning
TLDR
We propose a blind IQA model, which learns qualitative evaluations directly and outputs numerical scores for general utilization and fair comparison. Expand
Unsupervised video-shot segmentation and model-free anchorperson detection for news video story parsing
  • Xinbo Gao, X. Tang
  • Computer Science
  • IEEE Trans. Circuits Syst. Video Technol.
  • 1 September 2002
TLDR
An unsupervised fuzzy c-means algorithm is used to detect video-shot boundaries in order to segment a news video into video shots. Expand
Learning Multiple Linear Mappings for Efficient Single Image Super-Resolution
TLDR
We propose a novel computationally efficient single image SR method that learns multiple linear mappings (MLM) to directly transform LR feature subspaces into HR subspace. Expand
Image Quality Assessment Based on Multiscale Geometric Analysis
TLDR
A novel reduced-reference image quality assessment framework is proposed by incorporating merits of multiscale geometry analysis (MGA), contrast sensitivity function (CSF), and the Weber’s law of just noticeable difference (JND). Expand
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