转载自https://zhuanlan.zhihu.com/p/180551773

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ECCV2020｜图像重建/底层视觉(超分辨率，图像恢复，去雨，去雾，去模糊，去噪等)相关论文汇总（附论文链接/开源代码/解析）【持续更新】_Kobaayyy的博客-CSDN博客_eccv2020去雨​

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整理了下今年ECCV图像重建/底层视觉(Low-Level Vision)相关的一些论文，包括超分辨率，图像恢复，去雨，去雾，去模糊，去噪等方向。大家如果觉得有帮助，欢迎点赞和收藏~~

最新修改版本会首先更新在Github，欢迎star~

https://github.com/Kobaayyy/Awesome-ECCV2020-Low-Level-Vision​github.com

 

2020年ECCV（European Conference on Computer Vision）将于8月2日到8月28日在线上召开。目前ECCV2020已经放榜，有效投稿数为5025，最终收录1361篇论文，录取率是27%。其中104篇 Oral、161篇 Spotlights，其余的均为Poster。
ECCV2020的官网：https://eccv2020.eu/
ECCV2020接收论文列表：https://eccv2020.eu/accepted-papers/

【Contents】

• 1.超分辨率（Super-Resolution)
• 2.图像去雨（Image Deraining）
• 3.图像去雾（Image Dehazing）
• 4.去模糊（Deblurring）
• 5.去噪（Denoising）
• 6.图像恢复（Image Restoration）
• 7.图像增强（Image Enhancement）
• 8.图像去摩尔纹（Image Demoireing）
• 9.图像修复（Inpainting）
• 10.图像质量评价（Image Quality Assessment）

1.超分辨率（Super-Resolution）

图像超分辨率

Invertible Image Rescaling

• Paper：https://arxiv.org/abs/2005.05650
• Code：https://github.com/pkuxmq/Invertible-Image-Rescaling
• Analysis：ECCV 2020 Oral | 可逆图像缩放：完美恢复降采样后的高清图片

Component Divide-and-Conquer for Real-World Image Super-Resolution

• Paper：https://arxiv.org/abs/2008.01928
• Code：https://github.com/xiezw5/Component-Divide-and-Conquer-for-Real-World-Image-Super-Resolution

SRFlow: Learning the Super-Resolution Space with Normalizing Flow

• Paper：https://arxiv.org/abs/2006.14200?context=eess
• Code：https://github.com/andreas128/SRFlow

Single Image Super-Resolution via a Holistic Attention Network

• Paper：https://arxiv.org/abs/2008.08767
• Code：https://github.com/wwlCape/HAN
• Analysis：ECCV2020最新图像超分辨重建文章

Stochastic Frequency Masking to Improve Super-Resolution and Denoising Networks

• Paper：https://arxiv.org/abs/2003.07119
• Code：https://github.com/majedelhelou/SFM

VarSR: Variational Super-Resolution Network for Very Low Resolution Images

• Paper：https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123680426.pdf

Learning with Privileged Information for Efficient Image Super-Resolutionq

• Paper：https://arxiv.org/abs/2007.07524
• Code：https://github.com/cvlab-yonsei/PISR
• Homepage：https://cvlab.yonsei.ac.kr/projects/PISR/

Binarized Neural Network for Single Image Super Resolution

• Paper：http://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123490086.pdf

Towards Content-independent Multi-Reference Super-Resolution: Adaptive Pattern Matching and Feature Aggregation

• Paper:http://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123700052.pdf

视频超分辨率

Across Scales & Across Dimensions: Temporal Super-Resolution using Deep Internal Learning

• Paper：https://arxiv.org/abs/2003.08872
• Code:https://github.com/eyalnaor/DeepTemporalSR
• Homepage：http://www.wisdom.weizmann.ac.il/~vision/DeepTemporalSR/

MuCAN: Multi-Correspondence Aggregation Network for Video Super-Resolution

• Paper：https://arxiv.org/abs/2007.11803v1

Video Super-Resolution with Recurrent Structure-Detail Network

• Paper：https://arxiv.org/abs/2008.00455
• Code：https://github.com/junpan19/RSDN
• Homepage：http://www.wisdom.weizmann.ac.il/~vision/DeepTemporalSR/

人脸超分辨率

Face Super-Resolution Guided by 3D Facial Priors

• Paper：https://arxiv.org/abs/2007.09454v1

光场图像超分辨率

Spatial-Angular Interaction for Light Field Image Super-Resolution

• Paper：https://arxiv.org/abs/1912.07849
• Code：https://github.com/YingqianWang/LF-InterNet
• Presentation：https://wyqdatabase.s3-us-west-1.amazonaws.com/LF-InterNet.mp4
• Analysis：ECCV 2020 | 空间-角度信息交互的光场图像超分辨，性能优异代码已开源

高光谱图像超分辨率

Cross-Attention in Coupled Unmixing Nets for Unsupervised Hyperspectral Super-Resolution

• Paper：https://arxiv.org/abs/2007.05230
• Code：https://github.com/danfenghong/ECCV2020_CUCaNet

零样本超分辨率

Zero-Shot Image Super-Resolution with Depth Guided Internal Degradation Learning

• Paper:http://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123620256.pdf

Fast Adaptation to Super-Resolution Networks via Meta-Learning

• Paper:https://arxiv.org/abs/2001.02905v1
• Code:https://github.com/parkseobin/MLSR

文本超分辨率

PlugNet: Degradation Aware Scene Text Recognition Supervised by a Pluggable Super-Resolution Unit

• Paper:http://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123600154.pdf
• Analysis：ECCV 2020 | 图匠数据、华中师范提出低质退化文本识别算法PlugNet

Scene Text Image Super-Resolution in the Wild

• Paper：https://arxiv.org/abs/2005.03341v1
• Code：https://github.com/JasonBoy1/TextZoom

绘画超分辨率

Texture Hallucination for Large-Factor Painting Super-Resolution

• Paper：https://arxiv.org/abs/1912.00515?context=eess.IV

超分辨率模型压缩/轻量化

Journey Towards Tiny Perceptual Super-Resolution

• Paper:https://arxiv.org/abs/2007.04356

LatticeNet: Towards Lightweight Image Super-resolution with Lattice Block

• Paper:http://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123670273.pdf

PAMS: Quantized Super-Resolution via Parameterized Max Scale

• Paper:https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123700562.pdf

标记超分

Mining self-similarity: Label super-resolution with epitomic representations

• Paper:https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123710528.pdf
• Code:https://github.com/anthonymlortiz/epitomes_lsr

2.图像去雨（Image Deraining）

Rethinking Image Deraining via Rain Streaks and Vapors

• Paper：https://arxiv.org/abs/2008.00823
• Code：https://github.com/yluestc/derain

Beyond Monocular Deraining: Paired Rain Removal Networks via Unpaired Semantic Understanding

• Paper：https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123720069.pdf

3.图像去雾（Image Dehazing）

HardGAN: A Haze-Aware Representation Distillation GAN for Single Image Dehazing

• Paper:https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510715.pdf

Physics-based Feature Dehazing Networks

• Paper:https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123750188.pdf

4.去模糊（Deblurring）

End-to-end Interpretable Learning of Non-blind Image Deblurring

• Paper：https://arxiv.org/abs/2007.01769
• Code：https://github.com/teboli/CPCR

Efficient Spatio-Temporal Recurrent Neural Network for Video Deblurring

• Paper：https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510188.pdf
• Code：https://github.com/zzh-tech/ESTRNN

Multi-Temporal Recurrent Neural Networks For Progressive Non-Uniform Single Image Deblurring With Incremental Temporal Training

• Paper：https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510324.pdf
• Code:https://github.com/Dong1P/MTRNN

Learning Event-Driven Video Deblurring and Interpolation

• Paper：https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123530681.pdf

Defocus Deblurring Using Dual-Pixel Data

• Paper：https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123550120.pdf
• Code:https://github.com/Abdullah-Abuolaim/defocus-deblurring-dual-pixel

Real-World Blur Dataset for Learning and Benchmarking Deblurring Algorithms

• Paper：https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123700188.pdf
• Code:https://github.com/rimchang/RealBlur

OID: Outlier Identifying and Discarding in Blind Image Deblurring

• Paper：https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123700596.pdf

Enhanced Sparse Model for Blind Deblurring

• Paper：https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123700630.pdf

5.去噪（Denoising）

Unpaired Learning of Deep Image Denoising

• Paper：https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123490341.pdf
• Code:https://github.com/XHWXD/DBSN

Practical Deep Raw Image Denoising on Mobile Devices

• Paper：https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510001.pdf

Reconstructing the Noise Variance Manifold for Image Denoising

• Paper：https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123540596.pdf

Burst Denoising via Temporally Shifted Wavelet Transforms

• Paper：https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123580239.pdf

Stochastic Frequency Masking to Improve Super-Resolution and Denoising Networks

• Paper：https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123610732.pdf
• Code：https://github.com/majedelhelou/SFM

Learning Graph-Convolutional Representations for Point Cloud Denoising

• Paper：https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123650103.pdf
• Code：https://github.com/diegovalsesia/GPDNet

Spatial Hierarchy Aware Residual Pyramid Network for Time-of-Flight Depth Denoising

• Paper：https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123690035.pdf

A Decoupled Learning Scheme for Real-world Burst Denoising from Raw Images

• Paper：https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123700154.pdf

Spatial-Adaptive Network for Single Image Denoising

• Paper：https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123750171.pdf
• Code:https://github.com/JimmyChame/SADNet

6.图像恢复（Image Restoration）

Exploiting Deep Generative Prior for Versatile Image Restoration and Manipulation

• Paper：https://arxiv.org/abs/2003.13659
• Code：https://github.com/XingangPan/deep-generative-prior

Stacking Networks Dynamically for Image Restoration Based on the Plug-and-Play Framework

• Paper:https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123580443.pdf

LIRA: Lifelong Image Restoration from Unknown Blended Distortions

• Paper:https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123630596.pdf

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

• Paper:https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123650052.pdf
• Code：https://github.com/hejingwenhejingwen/CResMD

Microscopy Image Restoration with Deep Wiener-Kolmogorov filters

• Paper:https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123650188.pdf
• Code：https://github.com/vpronina/DeepWienerRestoration/

Fully Trainable and Interpretable Non-Local Sparse Models for Image Restoration

• Paper:https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123670239.pdf
• Code：https://github.com/bruno-31/groupsc

Learning Enriched Features for Real Image Restoration and Enhancement

• Paper:https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123700494.pdf
• Code：https://github.com/swz30/MIRNet

Learning Disentangled Feature Representation for Hybrid-distorted Image Restoration

• Paper:https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123740307.pdf

7.图像增强（Image Enhancement）

URIE: Universal Image Enhancement for Visual Recognition in the Wild

• Paper:https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123540715.pdf
• Code：https://github.com/taeyoungson/urie

Early Exit Or Not: Resource-Efficient Blind Quality Enhancement for Compressed Images

• Paper:https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123610273.pdf
• Code：https://github.com/RyanXingQL/RBQE

Global and Local Enhancement Networks For Paired and Unpaired Image Enhancement

• Paper:https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123700341.pdf

PieNet: Personalized Image Enhancement Network

• Paper:https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123750375.pdf

8.图像去摩尔纹（Image Demoireing）

Wavelet-Based Dual-Branch Neural Network for Image Demoireing

• Paper：https://arxiv.org/abs/2007.07173
• Analysis：#每日五分钟一读# Image Demoireing

9.图像修复（Inpainting）

Learning Joint Spatial-Temporal Transformations for Video Inpainting

• Paper：https://arxiv.org/abs/2007.10247
• Code：https://github.com/researchmm/STTN

Rethinking Image Inpainting via a Mutual Encoder-Decoder with Feature Equalizations

• Paper：https://arxiv.org/abs/2007.06929
• Code：https://github.com/KumapowerLIU/ECCV2020oralRethinking-Image-Inpainting-via-a-Mutual-Encoder-Decoder-with-Feature-Equalizations
• Analysis：ECCV2020(Oral) Rethinking image inpainting

High-Resolution Image Inpainting with Iterative Confidence Feedback and Guided Upsampling

• Paper：https://arxiv.org/abs/2005.11742v1
• Homepage：https://zengxianyu.github.io/iic/

Short-Term and Long-Term Context Aggregation Network for Video Inpainting

• Paper：https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123490698.pdf

Learning Object Placement by Inpainting for Compositional Data Augmentation

• Paper：https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123580562.pdf

DVI: Depth Guided Video Inpainting for Autonomous Driving

• Paper：https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123660001.pdf
• Code：https://github.com/sibozhang/Depth-Guided-Inpainting

VCNet: A Robust Approach to Blind Image Inpainting

• Paper：https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123700749.pdf
• Code：https://github.com/shepnerd/blindinpainting_vcnet

Guidance and Evaluation: Semantic-Aware Image Inpainting for Mixed Scenes

• Paper：https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123720681.pdf

10.图像质量评价（Image Quality Assessment）

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

• Paper:https://arxiv.org/pdf/2007.12142.pdf

GIQA: Generated Image Quality Assessment

• Paper：https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123700749.pdf
• Code：https://github.com/cientgu/GIQA

持续更新~

参考

[1] ECCV 2020 超分辨率方向上接收文章总结
[2] ECCV 2020 超分辨率方向上接收文章总结（持续更新）持续更新
[3] ECCV 2020 | 空间-角度信息交互的光场图像超分辨，性能优异代码已开源
[4] ECCV2020-Code
[5] ECCV 2020 | 图匠数据、华中师范提出低质退化文本识别算法PlugNet
[6] ECCV2020(Oral) Rethinking image inpainting
[7] ECCV 2020 Oral 论文汇总！
[8] #每日五分钟一读# Image Demoireing
码字不易，如果您觉得有帮助，欢迎点赞和收藏~~

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