b'Ding Liu'

research

∙ 05/19/2021

Retrieval-Augmented Transformer-XL for Close-Domain Dialog Generation

Transformer-based models have demonstrated excellent capabilities of cap...

Giovanni Bonetta, et al. ∙

research

∙ 05/08/2021

Understanding Neural Networks with Logarithm Determinant Entropy Estimator

Understanding the informative behaviour of deep neural networks is chall...

Zhanghao Zhouyin, et al. ∙

research

∙ 04/12/2021

Adversarial Open Domain Adaption for Sketch-to-Photo Synthesis

In this paper, we explore the open-domain sketch-to-photo translation, w...

Xiaoyu Xiang, et al. ∙

research

∙ 04/08/2021

Progressive Temporal Feature Alignment Network for Video Inpainting

Video inpainting aims to fill spatio-temporal "corrupted" regions with p...

Xueyan Zou, et al. ∙

research

∙ 12/07/2020

CompFeat: Comprehensive Feature Aggregation for Video Instance Segmentation

Video instance segmentation is a complex task in which we need to detect...

Yang Fu, et al. ∙

research

∙ 06/08/2020

Outlier Detection Using a Novel method: Quantum Clustering

We propose a new assumption in outlier detection: Normal data instances ...

Ding Liu, et al. ∙

research

∙ 06/08/2020

Neural Sparse Representation for Image Restoration

Inspired by the robustness and efficiency of sparse representation in sp...

Yuchen Fan, et al. ∙

research

∙ 05/15/2020

Quantum-Classical Machine learning by Hybrid Tensor Networks

Tensor networks (TN) have found a wide use in machine learning, and in p...

Ding Liu, et al. ∙

research

∙ 05/06/2020

Unsupervised Real-world Low-light Image Enhancement with Decoupled Networks

Conventional learning-based approaches to low-light image enhancement ty...

Wei Xiong, et al. ∙

research

∙ 04/28/2020

Pyramid Attention Networks for Image Restoration

Self-similarity refers to the image prior widely used in image restorati...

Yiqun Mei, et al. ∙

research

∙ 12/19/2019

Scale-wise Convolution for Image Restoration

While scale-invariant modeling has substantially boosted the performance...

Yuchen Fan, et al. ∙

research

∙ 12/07/2019

DAVID: Dual-Attentional Video Deblurring

Blind video deblurring restores sharp frames from a blurry sequence with...

Junru Wu, et al. ∙

research

∙ 11/09/2019

Information Bottleneck Methods on Convolutional Neural Networks

Recent year, many researches attempt to open the black box of deep neura...

Junjie Li, et al. ∙

research

∙ 06/17/2019

EnlightenGAN: Deep Light Enhancement without Paired Supervision

Deep learning-based methods have achieved remarkable success in image re...

Yifan Jiang, et al. ∙

research

∙ 03/26/2019

Generative Tensor Network Classification Model for Supervised Machine Learning

Tensor network (TN) has recently triggered extensive interests in develo...

Zheng-Zhi Sun, et al. ∙

research

∙ 09/06/2018

Connecting Image Denoising and High-Level Vision Tasks via Deep Learning

Image denoising and high-level vision tasks are usually handled independ...

Ding Liu, et al. ∙

research

∙ 07/29/2018

U-Finger: Multi-Scale Dilated Convolutional Network for Fingerprint Image Denoising and Inpainting

This paper studies the challenging problem of fingerprint image denoisin...

Ramakrishna Prabhu, et al. ∙

research

∙ 06/07/2018

Non-Local Recurrent Network for Image Restoration

Many classic methods have shown non-local self-similarity in natural ima...

Ding Liu, et al. ∙

research

∙ 05/07/2018

Image Super-Resolution via Dual-State Recurrent Networks

Advances in image super-resolution (SR) have recently benefited signific...

Wei Han, et al. ∙

research

∙ 04/19/2018

Survey of Face Detection on Low-quality Images

Face detection is a well-explored problem. Many challenges on face detec...

Yuqian Zhou, et al. ∙

research

∙ 04/16/2018

Learning Simple Thresholded Features with Sparse Support Recovery

The thresholded feature has recently emerged as an extremely efficient, ...

Zhangyang Wang, et al. ∙

research

∙ 12/20/2017

Enhance Visual Recognition under Adverse Conditions via Deep Networks

Visual recognition under adverse conditions is a very important and chal...

Ding Liu, et al. ∙

research

∙ 12/04/2017

Learning Object Detectors from Scratch with Gated Recurrent Feature Pyramids

In this paper, we propose gated recurrent feature pyramid for the proble...

Zhiqiang Shen, et al. ∙

research

∙ 10/13/2017

Machine Learning by Two-Dimensional Hierarchical Tensor Networks: A Quantum Information Theoretic Perspective on Deep Architectures

The resemblance between the methods used in studying quantum-many body p...

Ding Liu, et al. ∙

research

∙ 09/10/2017

Robust Emotion Recognition from Low Quality and Low Bit Rate Video: A Deep Learning Approach

Emotion recognition from facial expressions is tremendously useful, espe...

Bowen Cheng, et al. ∙

research

∙ 07/27/2017

Learning Audio Sequence Representations for Acoustic Event Classification

Acoustic Event Classification (AEC) has become a significant task for ma...

Zixing Zhang, et al. ∙

research

∙ 06/14/2017

When Image Denoising Meets High-Level Vision Tasks: A Deep Learning Approach

Conventionally, image denoising and high-level vision tasks are handled ...

Ding Liu, et al. ∙

research

∙ 02/27/2017

Understanding Convolution for Semantic Segmentation

Recent advances in deep learning, especially deep convolutional neural n...

Panqu Wang, et al. ∙

research

∙ 01/03/2017

Learning a Mixture of Deep Networks for Single Image Super-Resolution

Single image super-resolution (SR) is an ill-posed problem which aims to...

Ding Liu, et al. ∙

research

∙ 01/16/2016

Brain-Inspired Deep Networks for Image Aesthetics Assessment

Image aesthetics assessment has been challenging due to its subjective n...

Zhangyang Wang, et al. ∙

research

∙ 01/16/2016

Studying Very Low Resolution Recognition Using Deep Networks

Visual recognition research often assumes a sufficient resolution of the...

Zhangyang Wang, et al. ∙

research

∙ 01/16/2016

D^3: Deep Dual-Domain Based Fast Restoration of JPEG-Compressed Images

In this paper, we design a Deep Dual-Domain (D^3) based fast restoration...

Zhangyang Wang, et al. ∙

research

∙ 07/31/2015

Deep Networks for Image Super-Resolution with Sparse Prior

Deep learning techniques have been successfully applied in many areas of...

Zhaowen Wang, et al. ∙

Ding Liu

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