Search Results for author: Chao Dong

Found 100 papers, 52 papers with code

Scaling Up to Excellence: Practicing Model Scaling for Photo-Realistic Image Restoration In the Wild

no code implementations24 Jan 2024 Fanghua Yu, Jinjin Gu, Zheyuan Li, JinFan Hu, Xiangtao Kong, Xintao Wang, Jingwen He, Yu Qiao, Chao Dong

We introduce SUPIR (Scaling-UP Image Restoration), a groundbreaking image restoration method that harnesses generative prior and the power of model scaling up.

Descriptive Image Restoration

Towards Effective Multiple-in-One Image Restoration: A Sequential and Prompt Learning Strategy

1 code implementation7 Jan 2024 Xiangtao Kong, Chao Dong, Lei Zhang

While single task image restoration (IR) has achieved significant successes, it remains a challenging issue to train a single model which can tackle multiple IR tasks.

Image Restoration

Depicting Beyond Scores: Advancing Image Quality Assessment through Multi-modal Language Models

1 code implementation14 Dec 2023 Zhiyuan You, Zheyuan Li, Jinjin Gu, Zhenfei Yin, Tianfan Xue, Chao Dong

We introduce a Depicted image Quality Assessment method (DepictQA), overcoming the constraints of traditional score-based approaches.

Descriptive Image Quality Assessment +1

SmartEdit: Exploring Complex Instruction-based Image Editing with Multimodal Large Language Models

1 code implementation11 Dec 2023 Yuzhou Huang, Liangbin Xie, Xintao Wang, Ziyang Yuan, Xiaodong Cun, Yixiao Ge, Jiantao Zhou, Chao Dong, Rui Huang, Ruimao Zhang, Ying Shan

Both quantitative and qualitative results on this evaluation dataset indicate that our SmartEdit surpasses previous methods, paving the way for the practical application of complex instruction-based image editing.

A Comparative Study of Image Restoration Networks for General Backbone Network Design

1 code implementation18 Oct 2023 Xiangyu Chen, Zheyuan Li, Yuandong Pu, Yihao Liu, Jiantao Zhou, Yu Qiao, Chao Dong

Following this, we present the benchmark results and analyze the reasons behind the performance disparity of different models across various tasks.

Image Restoration

Unifying Image Processing as Visual Prompting Question Answering

no code implementations16 Oct 2023 Yihao Liu, Xiangyu Chen, Xianzheng Ma, Xintao Wang, Jiantao Zhou, Yu Qiao, Chao Dong

To address this issue, we propose a universal model for general image processing that covers image restoration, image enhancement, image feature extraction tasks, etc.

Image Enhancement Image Restoration +4

UAV Swarm Deployment and Trajectory for 3D Area Coverage via Reinforcement Learning

no code implementations21 Sep 2023 Jia He, Ziye Jia, Chao Dong, Junyu Liu, Qihui Wu, Jingxian Liu

Unmanned aerial vehicles (UAVs) are recognized as promising technologies for area coverage due to the flexibility and adaptability.


HAT: Hybrid Attention Transformer for Image Restoration

2 code implementations11 Sep 2023 Xiangyu Chen, Xintao Wang, Wenlong Zhang, Xiangtao Kong, Yu Qiao, Jiantao Zhou, Chao Dong

In the training stage, we additionally adopt a same-task pre-training strategy to further exploit the potential of the model for further improvement.

Image Compression Image Denoising +2

SEAL: A Framework for Systematic Evaluation of Real-World Super-Resolution

1 code implementation6 Sep 2023 Wenlong Zhang, Xiaohui Li, Xiangyu Chen, Yu Qiao, Xiao-Ming Wu, Chao Dong

In particular, we cluster the extensive degradation space to create a set of representative degradation cases, which serves as a comprehensive test set.


Routing Recovery for UAV Networks with Deliberate Attacks: A Reinforcement Learning based Approach

no code implementations14 Aug 2023 Sijie He, Ziye Jia, Chao Dong, Wei Wang, Yilu Cao, Yang Yang, Qihui Wu

The unmanned aerial vehicle (UAV) network is popular these years due to its various applications.

GET3D--: Learning GET3D from Unconstrained Image Collections

no code implementations27 Jul 2023 Fanghua Yu, Xintao Wang, Zheyuan Li, Yan-Pei Cao, Ying Shan, Chao Dong

While generative models have shown potential in creating 3D textured shapes from 2D images, their applicability in 3D industries is limited due to the lack of a well-defined camera distribution in real-world scenarios, resulting in low-quality shapes.

DeSRA: Detect and Delete the Artifacts of GAN-based Real-World Super-Resolution Models

1 code implementation5 Jul 2023 Liangbin Xie, Xintao Wang, Xiangyu Chen, Gen Li, Ying Shan, Jiantao Zhou, Chao Dong

After detecting the artifact regions, we develop a finetune procedure to improve GAN-based SR models with a few samples, so that they can deal with similar types of artifacts in more unseen real data.

Image Super-Resolution

Impact of UAVs Equipped with ADS-B on the Civil Aviation Monitoring System

no code implementations4 Jul 2023 Yiyang Liao, Lei Zhang, Ziye Jia, Chao Dong, Yifan Zhang, Qihui Wu, Huiling Hu, Bin Wang

However, due to the limited frequency of ADS-B technique, UAVs equipped with ADS-B devices result in the loss of packets to both UAVs and civil aviation.

Blocking Position

Crafting Training Degradation Distribution for the Accuracy-Generalization Trade-off in Real-World Super-Resolution

no code implementations29 May 2023 Ruofan Zhang, Jinjin Gu, Haoyu Chen, Chao Dong, Yulun Zhang, Wenming Yang

In this work, we introduce a novel approach to craft training degradation distributions using a small set of reference images.


Masked Image Training for Generalizable Deep Image Denoising

1 code implementation CVPR 2023 Haoyu Chen, Jinjin Gu, Yihao Liu, Salma Abdel Magid, Chao Dong, Qiong Wang, Hanspeter Pfister, Lei Zhu

To address this issue, we present a novel approach to enhance the generalization performance of denoising networks, known as masked training.

Image Denoising

TextIR: A Simple Framework for Text-based Editable Image Restoration

no code implementations28 Feb 2023 Yunpeng Bai, Cairong Wang, Shuzhao Xie, Chao Dong, Chun Yuan, Zhi Wang

We use the text-image feature compatibility of the CLIP to alleviate the difficulty of fusing text and image features.

Colorization Image Colorization +3

Computation Offloading for Uncertain Marine Tasks by Cooperation of UAVs and Vessels

no code implementations13 Feb 2023 Jiahao You, Ziye Jia, Chao Dong, Lijun He, Yilu Cao, Qihui Wu

Then, we formulate the studied problem into a Markov decision process, aiming to minimize the total execution time and energy cost.


ITstyler: Image-optimized Text-based Style Transfer

no code implementations26 Jan 2023 Yunpeng Bai, Jiayue Liu, Chao Dong, Chun Yuan

Text-based style transfer is a newly-emerging research topic that uses text information instead of style image to guide the transfer process, significantly extending the application scenario of style transfer.

Style Transfer

Towards Arbitrary Text-driven Image Manipulation via Space Alignment

no code implementations25 Jan 2023 Yunpeng Bai, Zihan Zhong, Chao Dong, Weichen Zhang, Guowei Xu, Chun Yuan

Then, the text input can be directly accessed into the StyleGAN space and be used to find the semantic shift according to the text description.

Attribute Image Manipulation

DegAE: A New Pretraining Paradigm for Low-Level Vision

1 code implementation CVPR 2023 Yihao Liu, Jingwen He, Jinjin Gu, Xiangtao Kong, Yu Qiao, Chao Dong

However, we argue that pretraining is more significant for high-cost tasks, where data acquisition is more challenging.


Mitigating Artifacts in Real-World Video Super-Resolution Models

1 code implementation14 Dec 2022 Liangbin Xie, Xintao Wang, Shuwei Shi, Jinjin Gu, Chao Dong, Ying Shan

To aggregate a new hidden state that contains fewer artifacts from the hidden state pool, we devise a Selective Cross Attention (SCA) module, in which the attention between input features and each hidden state is calculated.

Video Super-Resolution

AnimeRun: 2D Animation Visual Correspondence from Open Source 3D Movies

1 code implementation10 Nov 2022 Li SiYao, Yuhang Li, Bo Li, Chao Dong, Ziwei Liu, Chen Change Loy

Existing correspondence datasets for two-dimensional (2D) cartoon suffer from simple frame composition and monotonic movements, making them insufficient to simulate real animations.

Optical Flow Estimation

UDC-UNet: Under-Display Camera Image Restoration via U-Shape Dynamic Network

1 code implementation5 Sep 2022 Xina Liu, JinFan Hu, Xiangyu Chen, Chao Dong

Particularly, flare and blur in UDC images could severely deteriorate the user experience in high dynamic range (HDR) scenes.

Image Restoration Tone Mapping

Recurrent LSTM-based UAV Trajectory Prediction with ADS-B Information

no code implementations1 Sep 2022 Yifan Zhang, Ziye Jia, Chao Dong, Yuntian Liu, Lei Zhang, Qihui Wu

It is noted that the recurrent neural network (RNN) is available for the UAV trajectory prediction, in which the long short-term memory (LSTM) is specialized in dealing with the time-series data.

Time Series Analysis Trajectory Prediction

A Survey on Collaborative DNN Inference for Edge Intelligence

no code implementations16 Jul 2022 Weiqing Ren, Yuben Qu, Chao Dong, Yuqian Jing, Hao Sun, Qihui Wu, Song Guo

With the vigorous development of artificial intelligence (AI), the intelligent applications based on deep neural network (DNN) change people's lifestyles and the production efficiency.

NTIRE 2022 Challenge on Perceptual Image Quality Assessment

no code implementations23 Jun 2022 Jinjin Gu, Haoming Cai, Chao Dong, Jimmy S. Ren, Radu Timofte

This challenge is divided into two tracks, a full-reference IQA track similar to the previous NTIRE IQA challenge and a new track that focuses on the no-reference IQA methods.

Image Quality Assessment Image Restoration

Wireless Deep Video Semantic Transmission

no code implementations26 May 2022 Sixian Wang, Jincheng Dai, Zijian Liang, Kai Niu, Zhongwei Si, Chao Dong, Xiaoqi Qin, Ping Zhang

In this paper, we design a new class of high-efficiency deep joint source-channel coding methods to achieve end-to-end video transmission over wireless channels.

NTIRE 2022 Challenge on High Dynamic Range Imaging: Methods and Results

no code implementations25 May 2022 Eduardo Pérez-Pellitero, Sibi Catley-Chandar, Richard Shaw, Aleš Leonardis, Radu Timofte, Zexin Zhang, Cen Liu, Yunbo Peng, Yue Lin, Gaocheng Yu, Jin Zhang, Zhe Ma, Hongbin Wang, Xiangyu Chen, Xintao Wang, Haiwei Wu, Lin Liu, Chao Dong, Jiantao Zhou, Qingsen Yan, Song Zhang, Weiye Chen, Yuhang Liu, Zhen Zhang, Yanning Zhang, Javen Qinfeng Shi, Dong Gong, Dan Zhu, Mengdi Sun, Guannan Chen, Yang Hu, Haowei Li, Baozhu Zou, Zhen Liu, Wenjie Lin, Ting Jiang, Chengzhi Jiang, Xinpeng Li, Mingyan Han, Haoqiang Fan, Jian Sun, Shuaicheng Liu, Juan Marín-Vega, Michael Sloth, Peter Schneider-Kamp, Richard Röttger, Chunyang Li, Long Bao, Gang He, Ziyao Xu, Li Xu, Gen Zhan, Ming Sun, Xing Wen, Junlin Li, Shuang Feng, Fei Lei, Rui Liu, Junxiang Ruan, Tianhong Dai, Wei Li, Zhan Lu, Hengyan Liu, Peian Huang, Guangyu Ren, Yonglin Luo, Chang Liu, Qiang Tu, Fangya Li, Ruipeng Gang, Chenghua Li, Jinjing Li, Sai Ma, Chenming Liu, Yizhen Cao, Steven Tel, Barthelemy Heyrman, Dominique Ginhac, Chul Lee, Gahyeon Kim, Seonghyun Park, An Gia Vien, Truong Thanh Nhat Mai, Howoon Yoon, Tu Vo, Alexander Holston, Sheir Zaheer, Chan Y. Park

The challenge is composed of two tracks with an emphasis on fidelity and complexity constraints: In Track 1, participants are asked to optimize objective fidelity scores while imposing a low-complexity constraint (i. e. solutions can not exceed a given number of operations).

Image Restoration Vocal Bursts Intensity Prediction

Evaluating the Generalization Ability of Super-Resolution Networks

no code implementations14 May 2022 Yihao Liu, Hengyuan Zhao, Jinjin Gu, Yu Qiao, Chao Dong

However, research on the generalization ability of Super-Resolution (SR) networks is currently absent.


VQFR: Blind Face Restoration with Vector-Quantized Dictionary and Parallel Decoder

1 code implementation13 May 2022 YuChao Gu, Xintao Wang, Liangbin Xie, Chao Dong, Gen Li, Ying Shan, Ming-Ming Cheng

Equipped with the VQ codebook as a facial detail dictionary and the parallel decoder design, the proposed VQFR can largely enhance the restored quality of facial details while keeping the fidelity to previous methods.

Blind Face Restoration Quantization

Blueprint Separable Residual Network for Efficient Image Super-Resolution

1 code implementation12 May 2022 Zheyuan Li, Yingqi Liu, Xiangyu Chen, Haoming Cai, Jinjin Gu, Yu Qiao, Chao Dong

One is the usage of blueprint separable convolution (BSConv), which takes place of the redundant convolution operation.

Image Super-Resolution

RepSR: Training Efficient VGG-style Super-Resolution Networks with Structural Re-Parameterization and Batch Normalization

no code implementations11 May 2022 Xintao Wang, Chao Dong, Ying Shan

Extensive experiments demonstrate that our simple RepSR is capable of achieving superior performance to previous SR re-parameterization methods among different model sizes.


NTIRE 2022 Challenge on Efficient Super-Resolution: Methods and Results

2 code implementations11 May 2022 Yawei Li, Kai Zhang, Radu Timofte, Luc van Gool, Fangyuan Kong, Mingxi Li, Songwei Liu, Zongcai Du, Ding Liu, Chenhui Zhou, Jingyi Chen, Qingrui Han, Zheyuan Li, Yingqi Liu, Xiangyu Chen, Haoming Cai, Yu Qiao, Chao Dong, Long Sun, Jinshan Pan, Yi Zhu, Zhikai Zong, Xiaoxiao Liu, Zheng Hui, Tao Yang, Peiran Ren, Xuansong Xie, Xian-Sheng Hua, Yanbo Wang, Xiaozhong Ji, Chuming Lin, Donghao Luo, Ying Tai, Chengjie Wang, Zhizhong Zhang, Yuan Xie, Shen Cheng, Ziwei Luo, Lei Yu, Zhihong Wen, Qi Wu1, Youwei Li, Haoqiang Fan, Jian Sun, Shuaicheng Liu, Yuanfei Huang, Meiguang Jin, Hua Huang, Jing Liu, Xinjian Zhang, Yan Wang, Lingshun Long, Gen Li, Yuanfan Zhang, Zuowei Cao, Lei Sun, Panaetov Alexander, Yucong Wang, Minjie Cai, Li Wang, Lu Tian, Zheyuan Wang, Hongbing Ma, Jie Liu, Chao Chen, Yidong Cai, Jie Tang, Gangshan Wu, Weiran Wang, Shirui Huang, Honglei Lu, Huan Liu, Keyan Wang, Jun Chen, Shi Chen, Yuchun Miao, Zimo Huang, Lefei Zhang, Mustafa Ayazoğlu, Wei Xiong, Chengyi Xiong, Fei Wang, Hao Li, Ruimian Wen, Zhijing Yang, Wenbin Zou, Weixin Zheng, Tian Ye, Yuncheng Zhang, Xiangzhen Kong, Aditya Arora, Syed Waqas Zamir, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, Dandan Gaoand Dengwen Zhouand Qian Ning, Jingzhu Tang, Han Huang, YuFei Wang, Zhangheng Peng, Haobo Li, Wenxue Guan, Shenghua Gong, Xin Li, Jun Liu, Wanjun Wang, Dengwen Zhou, Kun Zeng, Hanjiang Lin, Xinyu Chen, Jinsheng Fang

The aim was to design a network for single image super-resolution that achieved improvement of efficiency measured according to several metrics including runtime, parameters, FLOPs, activations, and memory consumption while at least maintaining the PSNR of 29. 00dB on DIV2K validation set.

Image Super-Resolution

MM-RealSR: Metric Learning based Interactive Modulation for Real-World Super-Resolution

1 code implementation10 May 2022 Chong Mou, Yanze Wu, Xintao Wang, Chao Dong, Jian Zhang, Ying Shan

Instead of using known degradation levels as explicit supervision to the interactive mechanism, we propose a metric learning strategy to map the unquantifiable degradation levels in real-world scenarios to a metric space, which is trained in an unsupervised manner.

Image Restoration Metric Learning +1

A Closer Look at Blind Super-Resolution: Degradation Models, Baselines, and Performance Upper Bounds

no code implementations10 May 2022 Wenlong Zhang, Guangyuan Shi, Yihao Liu, Chao Dong, Xiao-Ming Wu

The recently proposed practical degradation model includes a full spectrum of degradation types, but only considers complex cases that use all degradation types in the degradation process, while ignoring many important corner cases that are common in the real world.

Blind Super-Resolution Super-Resolution

Activating More Pixels in Image Super-Resolution Transformer

2 code implementations CVPR 2023 Xiangyu Chen, Xintao Wang, Jiantao Zhou, Yu Qiao, Chao Dong

In the training stage, we additionally adopt a same-task pre-training strategy to exploit the potential of the model for further improvement.

Image Super-Resolution

GCFSR: a Generative and Controllable Face Super Resolution Method Without Facial and GAN Priors

no code implementations CVPR 2022 Jingwen He, Wu Shi, Kai Chen, Lean Fu, Chao Dong

The style modulation aims to generate realistic face details and the feature modulation dynamically fuses the multi-level encoded features and the generated ones conditioned on the upscaling factor.

Face Hallucination Hallucination +1

Reflash Dropout in Image Super-Resolution

no code implementations CVPR 2022 Xiangtao Kong, Xina Liu, Jinjin Gu, Yu Qiao, Chao Dong

Dropout is designed to relieve the overfitting problem in high-level vision tasks but is rarely applied in low-level vision tasks, like image super-resolution (SR).

Common Sense Reasoning Image Super-Resolution +1

Semantic-Sparse Colorization Network for Deep Exemplar-based Colorization

1 code implementation2 Dec 2021 Yunpeng Bai, Chao Dong, Zenghao Chai, Andong Wang, Zhengzhuo Xu, Chun Yuan

To address these two problems, we propose Semantic-Sparse Colorization Network (SSCN) to transfer both the global image style and detailed semantic-related colors to the gray-scale image in a coarse-to-fine manner.


Finding Discriminative Filters for Specific Degradations in Blind Super-Resolution

1 code implementation NeurIPS 2021 Liangbin Xie, Xintao Wang, Chao Dong, Zhongang Qi, Ying Shan

Unlike previous integral gradient methods, our FAIG aims at finding the most discriminative filters instead of input pixels/features for degradation removal in blind SR networks.

Blind Super-Resolution Super-Resolution

Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data

8 code implementations22 Jul 2021 Xintao Wang, Liangbin Xie, Chao Dong, Ying Shan

Though many attempts have been made in blind super-resolution to restore low-resolution images with unknown and complex degradations, they are still far from addressing general real-world degraded images.

Blind Super-Resolution Video Super-Resolution

RankSRGAN: Super Resolution Generative Adversarial Networks with Learning to Rank

no code implementations20 Jul 2021 Wenlong Zhang, Yihao Liu, Chao Dong, Yu Qiao

To address the problem, we propose Super-Resolution Generative Adversarial Networks with Ranker (RankSRGAN) to optimize generator in the direction of different perceptual metrics.

Image Super-Resolution Learning-To-Rank

Blind Image Super-Resolution: A Survey and Beyond

no code implementations7 Jul 2021 Anran Liu, Yihao Liu, Jinjin Gu, Yu Qiao, Chao Dong

This paper serves as a systematic review on recent progress in blind image SR, and proposes a taxonomy to categorize existing methods into three different classes according to their ways of degradation modelling and the data used for solving the SR model.

Image Super-Resolution

HDRUNet: Single Image HDR Reconstruction with Denoising and Dequantization

1 code implementation27 May 2021 Xiangyu Chen, Yihao Liu, Zhengwen Zhang, Yu Qiao, Chao Dong

In this work, we propose a novel learning-based approach using a spatially dynamic encoder-decoder network, HDRUNet, to learn an end-to-end mapping for single image HDR reconstruction with denoising and dequantization.

Denoising HDR Reconstruction +2

Decentralized Federated Learning for UAV Networks: Architecture, Challenges, and Opportunities

no code implementations15 Apr 2021 Yuben Qu, Haipeng Dai, Yan Zhuang, Jiafa Chen, Chao Dong, Fan Wu, Song Guo

Unmanned aerial vehicles (UAVs), or say drones, are envisioned to support extensive applications in next-generation wireless networks in both civil and military fields.

Federated Learning

Graph-Based Tri-Attention Network for Answer Ranking in CQA

no code implementations5 Mar 2021 Wei zhang, Zeyuan Chen, Chao Dong, Wen Wang, Hongyuan Zha, Jianyong Wang

However, they encounter two main limitations: (1) Correlations between answers in the same question are often overlooked.

Question Answering

Editorial: Introduction to the Issue on Deep Learning for Image/Video Restoration and Compression

no code implementations9 Feb 2021 A. Murat Tekalp, Michele Covell, Radu Timofte, Chao Dong

Recent works have shown that learned models can achieve significant performance gains, especially in terms of perceptual quality measures, over traditional methods.

Image Restoration Video Restoration

Image Quality Assessment for Perceptual Image Restoration: A New Dataset, Benchmark and Metric

no code implementations30 Nov 2020 Jinjin Gu, Haoming Cai, Haoyu Chen, Xiaoxing Ye, Jimmy Ren, Chao Dong

To answer the questions and promote the development of IQA methods, we contribute a large-scale IQA dataset, called Perceptual Image Processing ALgorithms (PIPAL) dataset.

Image Quality Assessment Image Restoration

Interpreting Super-Resolution Networks with Local Attribution Maps

no code implementations CVPR 2021 Jinjin Gu, Chao Dong

Based on LAM, we show that: (1) SR networks with a wider range of involved input pixels could achieve better performance.

Image Super-Resolution

Efficient Image Super-Resolution Using Pixel Attention

1 code implementation2 Oct 2020 Hengyuan Zhao, Xiangtao Kong, Jingwen He, Yu Qiao, Chao Dong

Pixel attention (PA) is similar as channel attention and spatial attention in formulation.

Image Super-Resolution

Conditional Sequential Modulation for Efficient Global Image Retouching

1 code implementation ECCV 2020 Jingwen He, Yihao Liu, Yu Qiao, Chao Dong

The base network acts like an MLP that processes each pixel independently and the condition network extracts the global features of the input image to generate a condition vector.

Image Retouching Photo Retouching

Understanding Deformable Alignment in Video Super-Resolution

no code implementations15 Sep 2020 Kelvin C. K. Chan, Xintao Wang, Ke Yu, Chao Dong, Chen Change Loy

Aside from the contributions to deformable alignment, our formulation inspires a more flexible approach to introduce offset diversity to flow-based alignment, improving its performance.

Optical Flow Estimation Video Super-Resolution

Enhanced Quadratic Video Interpolation

2 code implementations10 Sep 2020 Yihao Liu, Liangbin Xie, Li Si-Yao, Wenxiu Sun, Yu Qiao, Chao Dong

In this work, we further improve the performance of QVI from three facets and propose an enhanced quadratic video interpolation (EQVI) model.

Super-Resolution Video Frame Interpolation

Empowering the Edge Intelligence by Air-Ground Integrated Federated Learning in 6G Networks

no code implementations26 Jul 2020 Yuben Qu, Chao Dong, Jianchao Zheng, Qihui Wu, Yun Shen, Fan Wu, Alagan Anpalagan

Ubiquitous intelligence has been widely recognized as a critical vision of the future sixth generation (6G) networks, which implies the intelligence over the whole network from the core to the edge including end devices.

Networking and Internet Architecture

Video Super Resolution Based on Deep Learning: A Comprehensive Survey

no code implementations25 Jul 2020 Hongying Liu, Zhubo Ruan, Peng Zhao, Chao Dong, Fanhua Shang, Yuanyuan Liu, Linlin Yang, Radu Timofte

To the best of our knowledge, this work is the first systematic review on VSR tasks, and it is expected to make a contribution to the development of recent studies in this area and potentially deepen our understanding to the VSR techniques based on deep learning.

speech-recognition Speech Recognition +1

PIPAL: a Large-Scale Image Quality Assessment Dataset for Perceptual Image Restoration

no code implementations ECCV 2020 Jinjin Gu, Haoming Cai, Haoyu Chen, Xiaoxing Ye, Jimmy Ren, Chao Dong

To answer these questions and promote the development of IQA methods, we contribute a large-scale IQA dataset, called Perceptual Image Processing Algorithms (PIPAL) dataset.

Image Quality Assessment Image Restoration +1

Interactive Multi-Dimension Modulation with Dynamic Controllable Residual Learning for Image Restoration

1 code implementation ECCV 2020 Jingwen He, Chao Dong, Yu Qiao

To make a step forward, this paper presents a new problem setup, called multi-dimension (MD) modulation, which aims at modulating output effects across multiple degradation types and levels.

Image Restoration Test

Attentive Representation Learning with Adversarial Training for Short Text Clustering

no code implementations8 Dec 2019 Wei Zhang, Chao Dong, Jianhua Yin, Jianyong Wang

Relying on this, the representation learning and clustering for short texts are seamlessly integrated into a unified model.

Clustering Information Retrieval +3

RankSRGAN: Generative Adversarial Networks with Ranker for Image Super-Resolution

2 code implementations ICCV 2019 Wenlong Zhang, Yihao Liu, Chao Dong, Yu Qiao

To address the problem, we propose Super-Resolution Generative Adversarial Networks with Ranker (RankSRGAN) to optimize generator in the direction of perceptual metrics.

Image Super-Resolution

Suppressing Model Overfitting for Image Super-Resolution Networks

no code implementations11 Jun 2019 Ruicheng Feng, Jinjin Gu, Yu Qiao, Chao Dong

Large deep networks have demonstrated competitive performance in single image super-resolution (SISR), with a huge volume of data involved.

Image Super-Resolution Memorization

Rethinking Learning-based Demosaicing, Denoising, and Super-Resolution Pipeline

1 code implementation7 May 2019 Guocheng Qian, Yuanhao Wang, Jinjin Gu, Chao Dong, Wolfgang Heidrich, Bernard Ghanem, Jimmy S. Ren

In this work, we comprehensively study the effects of pipelines on the mixture problem of learning-based DN, DM, and SR, in both sequential and joint solutions.

Demosaicking Denoising +1

EDVR: Video Restoration with Enhanced Deformable Convolutional Networks

11 code implementations7 May 2019 Xintao Wang, Kelvin C. K. Chan, Ke Yu, Chao Dong, Chen Change Loy

In this work, we propose a novel Video Restoration framework with Enhanced Deformable networks, termed EDVR, to address these challenges.

Deblurring Video Enhancement +2

Path-Restore: Learning Network Path Selection for Image Restoration

1 code implementation23 Apr 2019 Ke Yu, Xintao Wang, Chao Dong, Xiaoou Tang, Chen Change Loy

To leverage this, we propose Path-Restore, a multi-path CNN with a pathfinder that can dynamically select an appropriate route for each image region.

Denoising Image Restoration +1

Modulating Image Restoration with Continual Levels via Adaptive Feature Modification Layers

1 code implementation CVPR 2019 Jingwen He, Chao Dong, Yu Qiao

In image restoration tasks, like denoising and super resolution, continual modulation of restoration levels is of great importance for real-world applications, but has failed most of existing deep learning based image restoration methods.

Image Denoising Image Restoration +1

Blind Super-Resolution With Iterative Kernel Correction

3 code implementations CVPR 2019 Jinjin Gu, Hannan Lu, WangMeng Zuo, Chao Dong

In this paper, we propose an Iterative Kernel Correction (IKC) method for blur kernel estimation in blind SR problem, where the blur kernels are unknown.

Blind Super-Resolution Image Super-Resolution

Deep Network Interpolation for Continuous Imagery Effect Transition

2 code implementations CVPR 2019 Xintao Wang, Ke Yu, Chao Dong, Xiaoou Tang, Chen Change Loy

Deep convolutional neural network has demonstrated its capability of learning a deterministic mapping for the desired imagery effect.

Image Restoration Image-to-Image Translation +2

Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

1 code implementation5 Nov 2018 Spyridon Bakas, Mauricio Reyes, Andras Jakab, Stefan Bauer, Markus Rempfler, Alessandro Crimi, Russell Takeshi Shinohara, Christoph Berger, Sung Min Ha, Martin Rozycki, Marcel Prastawa, Esther Alberts, Jana Lipkova, John Freymann, Justin Kirby, Michel Bilello, Hassan Fathallah-Shaykh, Roland Wiest, Jan Kirschke, Benedikt Wiestler, Rivka Colen, Aikaterini Kotrotsou, Pamela Lamontagne, Daniel Marcus, Mikhail Milchenko, Arash Nazeri, Marc-Andre Weber, Abhishek Mahajan, Ujjwal Baid, Elizabeth Gerstner, Dongjin Kwon, Gagan Acharya, Manu Agarwal, Mahbubul Alam, Alberto Albiol, Antonio Albiol, Francisco J. Albiol, Varghese Alex, Nigel Allinson, Pedro H. A. Amorim, Abhijit Amrutkar, Ganesh Anand, Simon Andermatt, Tal Arbel, Pablo Arbelaez, Aaron Avery, Muneeza Azmat, Pranjal B., W Bai, Subhashis Banerjee, Bill Barth, Thomas Batchelder, Kayhan Batmanghelich, Enzo Battistella, Andrew Beers, Mikhail Belyaev, Martin Bendszus, Eze Benson, Jose Bernal, Halandur Nagaraja Bharath, George Biros, Sotirios Bisdas, James Brown, Mariano Cabezas, Shilei Cao, Jorge M. Cardoso, Eric N Carver, Adrià Casamitjana, Laura Silvana Castillo, Marcel Catà, Philippe Cattin, Albert Cerigues, Vinicius S. Chagas, Siddhartha Chandra, Yi-Ju Chang, Shiyu Chang, Ken Chang, Joseph Chazalon, Shengcong Chen, Wei Chen, Jefferson W. Chen, Zhaolin Chen, Kun Cheng, Ahana Roy Choudhury, Roger Chylla, Albert Clérigues, Steven Colleman, Ramiro German Rodriguez Colmeiro, Marc Combalia, Anthony Costa, Xiaomeng Cui, Zhenzhen Dai, Lutao Dai, Laura Alexandra Daza, Eric Deutsch, Changxing Ding, Chao Dong, Shidu Dong, Wojciech Dudzik, Zach Eaton-Rosen, Gary Egan, Guilherme Escudero, Théo Estienne, Richard Everson, Jonathan Fabrizio, Yong Fan, Longwei Fang, Xue Feng, Enzo Ferrante, Lucas Fidon, Martin Fischer, Andrew P. French, Naomi Fridman, Huan Fu, David Fuentes, Yaozong Gao, Evan Gates, David Gering, Amir Gholami, Willi Gierke, Ben Glocker, Mingming Gong, Sandra González-Villá, T. Grosges, Yuanfang Guan, Sheng Guo, Sudeep Gupta, Woo-Sup Han, Il Song Han, Konstantin Harmuth, Huiguang He, Aura Hernández-Sabaté, Evelyn Herrmann, Naveen Himthani, Winston Hsu, Cheyu Hsu, Xiaojun Hu, Xiaobin Hu, Yan Hu, Yifan Hu, Rui Hua, Teng-Yi Huang, Weilin Huang, Sabine Van Huffel, Quan Huo, Vivek HV, Khan M. Iftekharuddin, Fabian Isensee, Mobarakol Islam, Aaron S. Jackson, Sachin R. Jambawalikar, Andrew Jesson, Weijian Jian, Peter Jin, V Jeya Maria Jose, Alain Jungo, B Kainz, Konstantinos Kamnitsas, Po-Yu Kao, Ayush Karnawat, Thomas Kellermeier, Adel Kermi, Kurt Keutzer, Mohamed Tarek Khadir, Mahendra Khened, Philipp Kickingereder, Geena Kim, Nik King, Haley Knapp, Urspeter Knecht, Lisa Kohli, Deren Kong, Xiangmao Kong, Simon Koppers, Avinash Kori, Ganapathy Krishnamurthi, Egor Krivov, Piyush Kumar, Kaisar Kushibar, Dmitrii Lachinov, Tryphon Lambrou, Joon Lee, Chengen Lee, Yuehchou Lee, M Lee, Szidonia Lefkovits, Laszlo Lefkovits, James Levitt, Tengfei Li, Hongwei Li, Hongyang Li, Xiaochuan Li, Yuexiang Li, Heng Li, Zhenye Li, Xiaoyu Li, Zeju Li, Xiaogang Li, Wenqi Li, Zheng-Shen Lin, Fengming Lin, Pietro Lio, Chang Liu, Boqiang Liu, Xiang Liu, Mingyuan Liu, Ju Liu, Luyan Liu, Xavier Llado, Marc Moreno Lopez, Pablo Ribalta Lorenzo, Zhentai Lu, Lin Luo, Zhigang Luo, Jun Ma, Kai Ma, Thomas Mackie, Anant Madabushi, Issam Mahmoudi, Klaus H. Maier-Hein, Pradipta Maji, CP Mammen, Andreas Mang, B. S. Manjunath, Michal Marcinkiewicz, S McDonagh, Stephen McKenna, Richard McKinley, Miriam Mehl, Sachin Mehta, Raghav Mehta, Raphael Meier, Christoph Meinel, Dorit Merhof, Craig Meyer, Robert Miller, Sushmita Mitra, Aliasgar Moiyadi, David Molina-Garcia, Miguel A. B. Monteiro, Grzegorz Mrukwa, Andriy Myronenko, Jakub Nalepa, Thuyen Ngo, Dong Nie, Holly Ning, Chen Niu, Nicholas K Nuechterlein, Eric Oermann, Arlindo Oliveira, Diego D. C. Oliveira, Arnau Oliver, Alexander F. I. Osman, Yu-Nian Ou, Sebastien Ourselin, Nikos Paragios, Moo Sung Park, Brad Paschke, J. Gregory Pauloski, Kamlesh Pawar, Nick Pawlowski, Linmin Pei, Suting Peng, Silvio M. Pereira, Julian Perez-Beteta, Victor M. Perez-Garcia, Simon Pezold, Bao Pham, Ashish Phophalia, Gemma Piella, G. N. Pillai, Marie Piraud, Maxim Pisov, Anmol Popli, Michael P. Pound, Reza Pourreza, Prateek Prasanna, Vesna Prkovska, Tony P. Pridmore, Santi Puch, Élodie Puybareau, Buyue Qian, Xu Qiao, Martin Rajchl, Swapnil Rane, Michael Rebsamen, Hongliang Ren, Xuhua Ren, Karthik Revanuru, Mina Rezaei, Oliver Rippel, Luis Carlos Rivera, Charlotte Robert, Bruce Rosen, Daniel Rueckert, Mohammed Safwan, Mostafa Salem, Joaquim Salvi, Irina Sanchez, Irina Sánchez, Heitor M. Santos, Emmett Sartor, Dawid Schellingerhout, Klaudius Scheufele, Matthew R. Scott, Artur A. Scussel, Sara Sedlar, Juan Pablo Serrano-Rubio, N. Jon Shah, Nameetha Shah, Mazhar Shaikh, B. Uma Shankar, Zeina Shboul, Haipeng Shen, Dinggang Shen, Linlin Shen, Haocheng Shen, Varun Shenoy, Feng Shi, Hyung Eun Shin, Hai Shu, Diana Sima, M Sinclair, Orjan Smedby, James M. Snyder, Mohammadreza Soltaninejad, Guidong Song, Mehul Soni, Jean Stawiaski, Shashank Subramanian, Li Sun, Roger Sun, Jiawei Sun, Kay Sun, Yu Sun, Guoxia Sun, Shuang Sun, Yannick R Suter, Laszlo Szilagyi, Sanjay Talbar, DaCheng Tao, Zhongzhao Teng, Siddhesh Thakur, Meenakshi H Thakur, Sameer Tharakan, Pallavi Tiwari, Guillaume Tochon, Tuan Tran, Yuhsiang M. Tsai, Kuan-Lun Tseng, Tran Anh Tuan, Vadim Turlapov, Nicholas Tustison, Maria Vakalopoulou, Sergi Valverde, Rami Vanguri, Evgeny Vasiliev, Jonathan Ventura, Luis Vera, Tom Vercauteren, C. A. Verrastro, Lasitha Vidyaratne, Veronica Vilaplana, Ajeet Vivekanandan, Qian Wang, Chiatse J. Wang, Wei-Chung Wang, Duo Wang, Ruixuan Wang, Yuanyuan Wang, Chunliang Wang, Guotai Wang, Ning Wen, Xin Wen, Leon Weninger, Wolfgang Wick, Shaocheng Wu, Qiang Wu, Yihong Wu, Yong Xia, Yanwu Xu, Xiaowen Xu, Peiyuan Xu, Tsai-Ling Yang, Xiaoping Yang, Hao-Yu Yang, Junlin Yang, Haojin Yang, Guang Yang, Hongdou Yao, Xujiong Ye, Changchang Yin, Brett Young-Moxon, Jinhua Yu, Xiangyu Yue, Songtao Zhang, Angela Zhang, Kun Zhang, Xue-jie Zhang, Lichi Zhang, Xiaoyue Zhang, Yazhuo Zhang, Lei Zhang, Jian-Guo Zhang, Xiang Zhang, Tianhao Zhang, Sicheng Zhao, Yu Zhao, Xiaomei Zhao, Liang Zhao, Yefeng Zheng, Liming Zhong, Chenhong Zhou, Xiaobing Zhou, Fan Zhou, Hongtu Zhu, Jin Zhu, Ying Zhuge, Weiwei Zong, Jayashree Kalpathy-Cramer, Keyvan Farahani, Christos Davatzikos, Koen van Leemput, Bjoern Menze

This study assesses the state-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i. e., 2012-2018.

Brain Tumor Segmentation Survival Prediction +1

Hierarchical multi-class segmentation of glioma images using networks with multi-level activation function

no code implementations22 Oct 2018 Xiaobin Hu, Hongwei Li, Yu Zhao, Chao Dong, Bjoern H. Menze, Marie Piraud

Based on the same start-of-the-art network architecture, the accuracy of nested-class (enhancing tumor) is reasonably improved from 69% to 72% compared with the traditional Softmax-based method which blind to topological prior.

Brain Tumor Segmentation Tumor Segmentation

Unsupervised Image Super-Resolution using Cycle-in-Cycle Generative Adversarial Networks

1 code implementation3 Sep 2018 Yuan Yuan, Siyuan Liu, Jiawei Zhang, Yongbing Zhang, Chao Dong, Liang Lin

We consider the single image super-resolution problem in a more general case that the low-/high-resolution pairs and the down-sampling process are unavailable.

Image Super-Resolution Image-to-Image Translation +1

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

46 code implementations1 Sep 2018 Xintao Wang, Ke Yu, Shixiang Wu, Jinjin Gu, Yihao Liu, Chao Dong, Chen Change Loy, Yu Qiao, Xiaoou Tang

To further enhance the visual quality, we thoroughly study three key components of SRGAN - network architecture, adversarial loss and perceptual loss, and improve each of them to derive an Enhanced SRGAN (ESRGAN).

Face Hallucination Generative Adversarial Network +2

Deep Convolution Networks for Compression Artifacts Reduction

2 code implementations9 Aug 2016 Ke Yu, Chao Dong, Chen Change Loy, Xiaoou Tang

Lossy compression introduces complex compression artifacts, particularly blocking artifacts, ringing effects and blurring.

Blocking Transfer Learning

Accelerating the Super-Resolution Convolutional Neural Network

13 code implementations1 Aug 2016 Chao Dong, Chen Change Loy, Xiaoou Tang

As a successful deep model applied in image super-resolution (SR), the Super-Resolution Convolutional Neural Network (SRCNN) has demonstrated superior performance to the previous hand-crafted models either in speed and restoration quality.

Image Super-Resolution

Modeling Rich Contexts for Sentiment Classification with LSTM

no code implementations5 May 2016 Minlie Huang, Yujie Cao, Chao Dong

Sentiment analysis on social media data such as tweets and weibo has become a very important and challenging task.

Classification General Classification +2

Image Super-Resolution Using Deep Convolutional Networks

60 code implementations31 Dec 2014 Chao Dong, Chen Change Loy, Kaiming He, Xiaoou Tang

We further show that traditional sparse-coding-based SR methods can also be viewed as a deep convolutional network.

Image Super-Resolution Video Super-Resolution

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