168 citations · 1.8k across the 114 of their papers we have counts for
28 papers · 1 filter
Learned Block-based Hybrid Image Compression
Yaojun Wu, Xin Li, Zhizheng Zhang +2
Recent works on learned image compression perform encoding and decoding processes in a full-resolution manner, resulting in two problems when deployed for practical applications. F…
Deep Multi-Scale Features Learning for Distorted Image Quality Assessment
Wei Zhou, Zhibo Chen
Image quality assessment (IQA) aims to estimate human perception based image visual quality. Although existing deep neural networks (DNNs) have shown significant effectiveness for…
Improving Machine Reading Comprehension with Single-choice Decision and Transfer Learning
Yufan Jiang, Shuangzhi Wu, Jing Gong +5
Multi-choice Machine Reading Comprehension (MMRC) aims to select the correct answer from a set of options based on a given passage and question. Due to task specific of MMRC, it is…
Causal Contextual Prediction for Learned Image Compression
Zongyu Guo, Zhizheng Zhang, Runsen Feng +1
Over the past several years, we have witnessed impressive progress in the field of learned image compression. Recent learned image codecs are commonly based on autoencoders, that f…
Towards Scalable Distributed Training of Deep Learning on Public Cloud Clusters
Shaohuai Shi, Xianhao Zhou, Shutao Song +21
Distributed training techniques have been widely deployed in large-scale deep neural networks (DNNs) training on dense-GPU clusters. However, on public cloud clusters, due to the m…
Bayesian Spatio-Temporal Graph Convolutional Network for Traffic Forecasting
Jun Fu, Wei Zhou, Zhibo Chen
In traffic forecasting, graph convolutional networks (GCNs), which model traffic flows as spatio-temporal graphs, have achieved remarkable performance. However, existing GCN-based…
Uncertainty-Aware Few-Shot Image Classification
Zhizheng Zhang, Cuiling Lan, Wenjun Zeng +2
Few-shot image classification learns to recognize new categories from limited labelled data. Metric learning based approaches have been widely investigated, where a query sample is…
FAN: Frequency Aggregation Network for Real Image Super-resolution
Yingxue Pang, Xin Li, Xin Jin +4
Single image super-resolution (SISR) aims to recover the high-resolution (HR) image from its low-resolution (LR) input image. With the development of deep learning, SISR has achiev…
Sequential Reinforced 360-Degree Video Adaptive Streaming with Cross-user Attentive Network
Jun Fu, Zhibo Chen, Xiaoming Chen +1
In the tile-based 360-degree video streaming, predicting user's future viewpoints and developing adaptive bitrate (ABR) algorithms are essential for optimizing user's quality of ex…
Deep Local and Global Spatiotemporal Feature Aggregation for Blind Video Quality Assessment
Wei Zhou, Zhibo Chen
In recent years, deep learning has achieved promising success for multimedia quality assessment, especially for image quality assessment (IQA). However, since there exist more comp…
LIRA: Lifelong Image Restoration from Unknown Blended Distortions
Jianzhao Liu, Jianxin Lin, Xin Li +3
Most existing image restoration networks are designed in a disposable way and catastrophically forget previously learned distortions when trained on a new distortion removal task.…
Learning Disentangled Feature Representation for Hybrid-distorted Image Restoration
Xin Li, Xin Jin, Jianxin Lin +5
Hybrid-distorted image restoration (HD-IR) is dedicated to restore real distorted image that is degraded by multiple distortions. Existing HD-IR approaches usually ignore the inher…
Global Distance-distributions Separation for Unsupervised Person Re-identification
Xin Jin, Cuiling Lan, Wenjun Zeng +1
Supervised person re-identification (ReID) often has poor scalability and usability in real-world deployments due to domain gaps and the lack of annotations for the target domain d…
Feature Alignment and Restoration for Domain Generalization and Adaptation
Xin Jin, Cuiling Lan, Wenjun Zeng +1
For domain generalization (DG) and unsupervised domain adaptation (UDA), cross domain feature alignment has been widely explored to pull the feature distributions of different doma…
Beyond Triplet Loss: Meta Prototypical N-tuple Loss for Person Re-identification
Zhizheng Zhang, Cuiling Lan, Wenjun Zeng +2
Person Re-identification (ReID) aims at matching a person of interest across images. In convolutional neural network (CNN) based approaches, loss design plays a vital role in pulli…
Residual Squeeze-and-Excitation Network for Fast Image Deraining
Jun Fu, Jianfeng Xu, Kazuyuki Tasaka +1
Image deraining is an important image processing task as rain streaks not only severely degrade the visual quality of images but also significantly affect the performance of high-l…
Style Normalization and Restitution for Generalizable Person Re-identification
Xin Jin, Cuiling Lan, Wenjun Zeng +2
Existing fully-supervised person re-identification (ReID) methods usually suffer from poor generalization capability caused by domain gaps. The key to solving this problem lies in…
Multi-scale Grouped Dense Network for VVC Intra Coding
Xin Li, Simeng Sun, Zhizheng Zhang +1
Versatile Video Coding (H.266/VVC) standard achieves better image quality when keeping the same bits than any other conventional image codec, such as BPG, JPEG, and etc. However, i…
Learned Video Compression with Feature-level Residuals
Runsen Feng, Yaojun Wu, Zongyu Guo +3
In this paper, we present an end-to-end video compression network for P-frame challenge on CLIC. We focus on deep neural network (DNN) based video compression, and improve the curr…
3-D Context Entropy Model for Improved Practical Image Compression
Zongyu Guo, Yaojun Wu, Runsen Feng +2
In this paper, we present our image compression framework designed for CLIC 2020 competition. Our method is based on Variational AutoEncoder (VAE) architecture which is strengthene…
Blind Quality Assessment for Image Superresolution Using Deep Two-Stream Convolutional Networks
Wei Zhou, Qiuping Jiang, Yuwang Wang +2
Numerous image superresolution (SR) algorithms have been proposed for reconstructing high-resolution (HR) images from input images with lower spatial resolutions. However, effectiv…
TuiGAN: Learning Versatile Image-to-Image Translation with Two Unpaired Images
Jianxin Lin, Yingxue Pang, Yingce Xia +2
An unsupervised image-to-image translation (UI2I) task deals with learning a mapping between two domains without paired images. While existing UI2I methods usually require numerous…
Multi-Granularity Reference-Aided Attentive Feature Aggregation for Video-based Person Re-identification
Zhizheng Zhang, Cuiling Lan, Wenjun Zeng +1
Video-based person re-identification (reID) aims at matching the same person across video clips. It is a challenging task due to the existence of redundancy among frames, newly rev…
Prior-enlightened and Motion-robust Video Deblurring
Ya Zhou, Jianfeng Xu, Kazuyuki Tasaka +2
Various blur distortions in video will cause negative impact on both human viewing and video-based applications, which makes motion-robust deblurring methods urgently needed. Most…