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2.CVPR2021｜底层视觉(超分辨率，视频视频图像恢复，解析解析去雨，源码源码去雾等)相关论文汇总（附论文链接/代码/解析）[持续更新]
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CVPR｜底层视觉(超分辨率，全套webapp后台控制源码图像恢复，视频视频去雨，解析解析去雾等)相关论文汇总（附论文链接/代码/解析）[持续更新]

       本文汇总了年CVPR底层视觉领域的源码源码一些论文，涉及超分辨率、全套图像恢复、视频视频去雨、解析解析去雾、源码源码tutk源码去模糊、全套去噪、视频视频图像恢复、解析解析图像增强、源码源码图像去摩尔纹、curses源码图像修复、图像质量评价、插帧、视频/图像压缩以及其他多任务等方向。以下是freeipa源码部分论文的简介：

       1. 超分辨率相关：

       Unsupervised Degradation Representation Learning for Blind Super-Resolution

       Data-Free Knowledge Distillation For Image Super-Resolution

       AdderSR: Towards Energy Efficient Image Super-Resolution

       Exploring Sparsity in Image Super-Resolution for Efficient Inference

       ClassSR: A General Framework to Accelerate Super-Resolution Networks by Data Characteristic

       Cross-MPI: Cross-scale Stereo for Image Super-Resolution using Multiplane Images

       LAU-Net: Latitude Adaptive Upscaling Network for Omnidirectional Image Super-resolution

       Learning Continuous Image Representation with Local Implicit Image Function

       Temporal Modulation Network for Controllable Space-Time Video Super-Resolution

       Robust Reference-based Super-Resolution via C²-Matching

       GLEAN: Generative Latent Bank for Large-Factor Image Super-Resolution

       BasicVSR: The Search for Essential Components in Video Super-Resolution and Beyond

       Video Rescaling Networks with Joint Optimization Strategies for Downscaling and Upscaling

       MASA-SR: Matching Acceleration and Spatial Adaptation for Reference-Based Image Super-Resolution

       Flow-based Kernel Prior with Application to Blind Super-Resolution

       SRWarp: Generalized Image Super-Resolution under Arbitrary Transformation

       2. 图像去雨相关：

       Removing Raindrops and Rain Streaks in One Go

       From Rain Generation to Rain Removal

       Closing the Loop: Joint Rain Generation and Removal via Disentangled Image Translation

       3. 图像去雾相关：

       Learning to Restore Hazy Video: A New Real-World Dataset and A New Method

       ContrastiveLearning for Compact Single Image Dehazing

       4. 去模糊相关：

       DeFMO: Deblurring and Shape Recovery of Fast Moving Objects

       ARVo: Learning All-Range Volumetric Correspondence for Video Deblurring

       Towards Rolling Shutter Correction and Deblurring in Dynamic Scenes

       Explore Image Deblurring via Blur Kernel Space

       5. 去噪相关：

       Neighbor2Neighbor: Self-Supervised Denoising from Single Noisy Images

       NBNet: Noise Basis Learning for Image Denoising with Subspace Projection

       Beyond Joint Demosaicking and Denoising

       Deep Denoising of Flash and No-Flash Pairs for Photography in Low-Light Environments

       Invertible Denoising Network: A Light Solution for Real Noise Removal

       6. 图像恢复相关：

       Multi-Stage Progressive Image Restoration

       CT Film Recovery via Disentangling Geometric Deformation and Illumination Variation: Simulated Datasets and Deep Models

       Restoring Extremely Dark Images in Real Time

       Dual Pixel Exploration: Simultaneous Depth Estimation and Image Restoration

       Progressive Semantic-Aware Style Transformation for Blind Face Restoration

       Towards Real-World Blind Face Restoration with Generative Facial Prior

       7. 图像增强相关：

       Auto-Exposure Fusion for Single-Image Shadow Removal

       Learning Multi-Scale Photo Exposure Correction

       Robust Reflection Removal with Reflection-free Flash-only Cues

       Learning Temporal Consistency for Low Light Video Enhancement from Single Images

       Removing Diffraction Image Artifacts in Under-Display Camera via Dynamic Skip Connection Network

       From Shadow Generation to Shadow Removal

       8. 图像去摩尔纹相关：

       PD-GAN:Probabilistic Diverse GAN for Image Inpainting

       Generating Diverse Structure for Image Inpainting with Hierarchical VQ-VAE

       Image Inpainting with External-internal Learning and Monochromic Bottleneck

       Progressive Temporal Feature Alignment Network for Video Inpainting

       TransFill: Reference-guided Image Inpainting by Merging Multiple Color and Spatial Transformations

       9. 图像修复相关：

       Pre-Trained Image Processing Transformer

       Invertible Image Signal Processing

       以上论文涵盖了底层视觉领域的多个方向，旨在解决图像处理中的各种问题。如果您觉得本文内容有帮助，欢迎点赞和收藏，感谢您的支持！

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