806 lines
37 KiB
Markdown
806 lines
37 KiB
Markdown
# CVPR2024｜底层视觉相关论文汇总
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CVPR2024底层视觉(Low-Level Vision)相关的论文和代码，包括超分辨率，图像去雨，图像去雾，去模糊，去噪，图像恢复，图像增强，图像去摩尔纹，图像修复，图像质量评价，插帧，图像/视频压缩等任务，具体如下。
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https://zhuanlan.zhihu.com/p/684196283
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CVPR2024官网：https://cvpr.thecvf.com/Conferences/2024
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CVPR接收论文列表：https://cvpr.thecvf.com/Conferences/2024/AcceptedPapers
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CVPR完整论文库：https://openaccess.thecvf.com/CVPR2024
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开会时间：2024年6月17日-6月21日
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论文接收公布时间：2024年2月27日
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# 相关方法概览
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1.超分辨率(Super-Resolution)
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2.图像去雨(Image Deraining)
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3.图像去雾(Image Dehazing)
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4.去模糊(Deblurring)
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5.去噪(Denoising)
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6.图像恢复(Image Restoration)
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7.图像增强(Image Enhancement)
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8.图像修复(Inpainting)
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9.高动态范围成像(HDR Imaging)
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10.图像质量评价(Image Quality Assessment)
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11.插帧(Frame Interpolation)
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12.视频/图像压缩(Video/Image Compression)
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13.压缩图像质量增强(Compressed Image Quality Enhancement)
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14.图像去反光(Image Reflection Removal)
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15.图像去阴影(Image Shadow Removal)
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16.图像上色(Image Colorization)
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17.图像和谐化(Image Harmonization)
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18.视频稳相(Video Stabilization)
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19.图像融合(Image Fusion)
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20.其他任务(Others)
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## 1.超分辨率(Super-Resolution)
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**AdaBM: On-the-Fly Adaptive Bit Mapping for Image Super-Resolution**
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* Paper: https://arxiv.org/abs/2404.03296
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* Code: https://github.com/Cheeun/AdaBM
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**A Dynamic Kernel Prior Model for Unsupervised Blind Image Super-Resolution**
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* Paper: https://arxiv.org/abs/2404.15620
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* Code: https://github.com/XYLGroup/DKP
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**APISR: Anime Production Inspired Real-World Anime Super-Resolution**
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* Paper: https://arxiv.org/abs/2403.01598
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* Code: https://github.com/Kiteretsu77/APISR
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**Arbitrary-Scale Image Generation and Upsampling using Latent Diffusion Model and Implicit Neural Decoder**
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* Paper: https://arxiv.org/abs/2403.10255v1
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* Code: https://github.com/zhenshij/arbitrary-scale-diffusion
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**Beyond Image Super-Resolution for Image Recognition with Task-Driven Perceptual Loss**
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* Paper: https://arxiv.org/abs/2404.01692
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* Code: https://github.com/JaehaKim97/SR4IR
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**Bilateral Event Mining and Complementary for Event Stream Super-Resolution**
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* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Huang_Bilateral_Event_Mining_and_Complementary_for_Event_Stream_Super-Resolution_CVPR_2024_paper.html
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* Code: https://github.com/Lqm26/BMCNet-ESR
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**Boosting Flow-based Generative Super-Resolution Models via Learned Prior**
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* Paper: https://arxiv.org/abs/2403.10988
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* Code: https://github.com/liyuantsao/FlowSR-LP
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**Building Bridges across Spatial and Temporal Resolutions: Reference-Based Super-Resolution via Change Priors and Conditional Diffusion Model**
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* Paper: https://arxiv.org/abs/2403.17460
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* Code: https://github.com/dongrunmin/RefDiff
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**CAMixerSR: Only Details Need More “Attention”**
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* Paper: https://arxiv.org/abs/2402.19289
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* Code: https://github.com/icandle/CAMixerSR
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**CFAT: Unleashing Triangular Windows for Image Super-resolution**
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* Paper: https://arxiv.org/abs/2403.16143
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* Code: https://github.com/rayabhisek123/CFAT
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**Continuous Optical Zooming: A Benchmark for Arbitrary-Scale Image Super-Resolution in Real World**
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* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Fu_Continuous_Optical_Zooming_A_Benchmark_for_Arbitrary-Scale_Image_Super-Resolution_in_CVPR_2024_paper.html
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* Code: https://github.com/pf0607/COZ
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**CoSeR: Bridging Image and Language for Cognitive Super-Resolution**
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* Paper: https://arxiv.org/abs/2311.16512
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* Code: https://github.com/VINHYU/CoSeR
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**CDFormer: When Degradation Prediction Embraces Diffusion Model for Blind Image Super-Resolution**
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* Paper: https://arxiv.org/abs/2405.07648
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* Code: https://github.com/I2-Multimedia-Lab/CDFormer
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**CycleINR: Cycle Implicit Neural Representation for Arbitrary-Scale Volumetric Super-Resolution of Medical Data**
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* Paper: https://arxiv.org/abs/2404.04878
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* Code:
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**Diffusion-based Blind Text Image Super-Resolution**
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* Paper: https://arxiv.org/abs/2312.08886
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* Code: https://github.com/YuzheZhang-1999/DiffTSR
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**DiSR-NeRF: Diffusion-Guided View-Consistent Super-Resolution NeRF**
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* Paper: https://arxiv.org/abs/2404.00874
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* Code:
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**Image Processing GNN: Breaking Rigidity in Super-Resolution**
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* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Tian_Image_Processing_GNN_Breaking_Rigidity_in_Super-Resolution_CVPR_2024_paper.html
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* Code: https://github.com/huawei-noah/Efficient-Computing/tree/master/LowLevel/IPG
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**Latent Modulated Function for Computational Optimal Continuous Image Representation**
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* Paper: https://arxiv.org/abs/2404.16451
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* Code: https://github.com/HeZongyao/LMF
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**Learning Coupled Dictionaries from Unpaired Data for Image Super-Resolution**
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* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Wang_Learning_Coupled_Dictionaries_from_Unpaired_Data_for_Image_Super-Resolution_CVPR_2024_paper.html
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* Code:
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**Learning Large-Factor EM Image Super-Resolution with Generative Priors**
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* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Shou_Learning_Large-Factor_EM_Image_Super-Resolution_with_Generative_Priors_CVPR_2024_paper.html
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* Code: https://github.com/jtshou/GPEMSR
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**Low-Res Leads the Way: Improving Generalization for Super-Resolution by Self-Supervised Learning**
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* Paper: https://arxiv.org/abs/2403.02601
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* Code: https://github.com/haoyuc/LWay
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**Navigating Beyond Dropout: An Intriguing Solution towards Generalizable Image Super-Resolution**
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* Paper: https://arxiv.org/abs/2402.18929v2
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* Code: https://github.com/Dreamzz5/Simple-Align
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**Neural Super-Resolution for Real-time Rendering with Radiance Demodulation**
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* Paper: https://arxiv.org/abs/2308.06699
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* Code: https://github.com/Riga2/NSRD
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**Rethinking Diffusion Model for Multi-Contrast MRI Super-Resolution**
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* Paper: https://arxiv.org/abs/2404.04785
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* Code: https://github.com/GuangYuanKK/DiffMSR
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**SeD: Semantic-Aware Discriminator for Image Super-Resolution**
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* Paper: https://arxiv.org/abs/2402.19387
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* Code: https://github.com/lbc12345/SeD
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**SeeSR: Towards Semantics-Aware Real-World Image Super-Resolution**
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* Paper: https://arxiv.org/abs/2311.16518
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* Code: https://github.com/cswry/SeeSR
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**Self-Adaptive Reality-Guided Diffusion for Artifact-Free Super-Resolution**
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* Paper: https://arxiv.org/abs/2403.16643
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* Code: https://github.com/ProAirVerse/Self-Adaptive-Guidance-Diffusion
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**SinSR: Diffusion-Based Image Super-Resolution in a Single Step**
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* Paper: https://github.com/wyf0912/SinSR/blob/main/main.pdf
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* Code: https://github.com/wyf0912/SinSR
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**Super-Resolution Reconstruction from Bayer-Pattern Spike Streams**
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* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Dong_Super-Resolution_Reconstruction_from_Bayer-Pattern_Spike_Streams_CVPR_2024_paper.html
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* Code: https://github.com/csycdong/CSCSR
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**Text-guided Explorable Image Super-resolution**
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* Paper: https://arxiv.org/abs/2403.01124
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* Code:
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**Training Generative Image Super-Resolution Models by Wavelet-Domain Losses Enables Better Control of Artifacts**
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* Paper: https://arxiv.org/abs/2402.19215
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* Code: https://github.com/mandalinadagi/wgsr
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**Transcending the Limit of Local Window: Advanced Super-Resolution Transformer with Adaptive Token Dictionary**
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* Paper: https://arxiv.org/abs/2401.08209
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* Code: https://github.com/LabShuHangGU/Adaptive-Token-Dictionary
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**Uncertainty-Aware Source-Free Adaptive Image Super-Resolution with Wavelet Augmentation Transformer**
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* Paper: https://arxiv.org/abs/2303.17783
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* Code:
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**Universal Robustness via Median Randomized Smoothing for Real-World Super-Resolution**
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* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Chaouai_Universal_Robustness_via_Median_Randomized_Smoothing_for_Real-World_Super-Resolution_CVPR_2024_paper.html
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* Code:
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### Video Super-Resolution
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**Enhancing Video Super-Resolution via Implicit Resampling-based Alignment**
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* Paper: https://github.com/kai422/IART/blob/main/arxiv.pdf
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* Code: https://github.com/kai422/IART
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**FMA-Net: Flow-Guided Dynamic Filtering and Iterative Feature Refinement with Multi-Attention for Joint Video Super-Resolution and Deblurring**
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* Paper: https://arxiv.org/abs/2401.03707
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* Code: https://github.com/KAIST-VICLab/FMA-Net
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**Learning Spatial Adaptation and Temporal Coherence in Diffusion Models for Video Super-Resolution**
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* Paper: https://arxiv.org/abs/2403.17000
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* Code:
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**Upscale-A-Video: Temporal-Consistent Diffusion Model for Real-World Video Super-Resolution**
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* Paper: https://arxiv.org/abs/2312.06640
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* Code: https://github.com/sczhou/Upscale-A-Video
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**Video Super-Resolution Transformer with Masked Inter&Intra-Frame Attention**
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* Paper: https://arxiv.org/abs/2401.06312
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* Code: https://github.com/LabShuHangGU/MIA-VSR
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## 2.图像去雨(Image Deraining)
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**Bidirectional Multi-Scale Implicit Neural Representations for Image Deraining**
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* Paper: https://arxiv.org/abs/2404.01547
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* Code: https://github.com/cschenxiang/NeRD-Rain
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## 3.图像去雾(Image Dehazing)
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**A Semi-supervised Nighttime Dehazing Baseline with Spatial-Frequency Aware and Realistic Brightness Constraint**
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* Paper: https://arxiv.org/abs/2403.18548
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* Code: https://github.com/Xiaofeng-life/SFSNiD
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**Depth Information Assisted Collaborative Mutual Promotion Network for Single Image Dehazing**
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* Paper: https://arxiv.org/abs/2403.01105
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* Code:
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**ODCR: Orthogonal Decoupling Contrastive Regularization for Unpaired Image Dehazing**
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* Paper: https://arxiv.org/abs/2404.17825v1
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* Code:
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### Video Dehazing
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**Driving-Video Dehazing with Non-Aligned Regularization for Safety Assistance**
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* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Fan_Driving-Video_Dehazing_with_Non-Aligned_Regularization_for_Safety_Assistance_CVPR_2024_paper.html
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* Code:
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## 4.去模糊(Deblurring)
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**A Unified Framework for Microscopy Defocus Deblur with Multi-Pyramid Transformer and Contrastive Learning**
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* Paper: https://arxiv.org/abs/2403.02611
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* Code: https://github.com/PieceZhang/MPT-CataBlur
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**AdaRevD: Adaptive Patch Exiting Reversible Decoder Pushes the Limit of Image Deblurring**
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* Paper: https://github.com/INVOKERer/AdaRevD/blob/master/AdaRevD.pdf
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* Code: https://github.com/INVOKERer/AdaRevD
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**Blur2Blur: Blur Conversion for Unsupervised Image Deblurring on Unknown Domains**
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* Paper: https://arxiv.org/abs/2403.16205
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* Code: https://github.com/VinAIResearch/Blur2Blur
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**Fourier Priors-Guided Diffusion for Zero-Shot Joint Low-Light Enhancement and Deblurring**
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* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Lv_Fourier_Priors-Guided_Diffusion_for_Zero-Shot_Joint_Low-Light_Enhancement_and_Deblurring_CVPR_2024_paper.html
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* Code:
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**ID-Blau: Image Deblurring by Implicit Diffusion-based reBLurring AUgmentation**
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* Paper：https://arxiv.org/abs/2312.10998
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* Code: https://github.com/plusgood-steven/ID-Blau
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**LDP: Language-driven Dual-Pixel Image Defocus Deblurring Network**
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* Paper: https://arxiv.org/abs/2307.09815
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* Code: https://github.com/noxsine/LDP
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**Mitigating Motion Blur in Neural Radiance Fields with Events and Frames**
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* Paper: https://rpg.ifi.uzh.ch/docs/CVPR24_Cannici.pdf
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* Code: https://github.com/uzh-rpg/EvDeblurNeRF
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**Motion-adaptive Separable Collaborative Filters for Blind Motion Deblurring**
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* Paper: https://arxiv.org/abs/2404.13153
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* Code: https://github.com/ChengxuLiu/MISCFilter
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**Motion Blur Decomposition with Cross-shutter Guidance**
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* Paper: https://arxiv.org/abs/2404.01120
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* Code: https://github.com/jixiang2016/dualBR
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**Real-World Efficient Blind Motion Deblurring via Blur Pixel Discretization**
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* Paper: https://arxiv.org/abs/2404.12168
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* Code:
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**Spike-guided Motion Deblurring with Unknown Modal Spatiotemporal Alignment**
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* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Zhang_Spike-guided_Motion_Deblurring_with_Unknown_Modal_Spatiotemporal_Alignment_CVPR_2024_paper.html
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* Code: https://github.com/Leozhangjiyuan/UaSDN
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**Unsupervised Blind Image Deblurring Based on Self-Enhancement**
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* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Chen_Unsupervised_Blind_Image_Deblurring_Based_on_Self-Enhancement_CVPR_2024_paper.html
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* Code:
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### Video Deblurring
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**Blur-aware Spatio-temporal Sparse Transformer for Video Deblurring**
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* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Zhang_Blur-aware_Spatio-temporal_Sparse_Transformer_for_Video_Deblurring_CVPR_2024_paper.html
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* Code: https://github.com/huicongzhang/BSSTNet
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**EVS-assisted Joint Deblurring Rolling-Shutter Correction and Video Frame Interpolation through Sensor Inverse Modeling**
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* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Jiang_EVS-assisted_Joint_Deblurring_Rolling-Shutter_Correction_and_Video_Frame_Interpolation_through_CVPR_2024_paper.html
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* Code:
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**Frequency-aware Event-based Video Deblurring for Real-World Motion Blur**
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* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Kim_Frequency-aware_Event-based_Video_Deblurring_for_Real-World_Motion_Blur_CVPR_2024_paper.html
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* Code:
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**Latency Correction for Event-guided Deblurring and Frame Interpolation**
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* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Yang_Latency_Correction_for_Event-guided_Deblurring_and_Frame_Interpolation_CVPR_2024_paper.html
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****Code:
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## 5.去噪(Denoising)
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**LAN: Learning to Adapt Noise for Image Denoising**
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* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Kim_LAN_Learning_to_Adapt_Noise_for_Image_Denoising_CVPR_2024_paper.html
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* Code:
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**LED: A Large-scale Real-world Paired Dataset for Event Camera Denoising**
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* Paper: https://arxiv.org/abs/2405.19718
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* Code:
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**Robust Image Denoising through Adversarial Frequency Mixup**
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* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Ryou_Robust_Image_Denoising_through_Adversarial_Frequency_Mixup_CVPR_2024_paper.html
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* Code: https://github.com/dhryougit/AFM
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**Real-World Mobile Image Denoising Dataset with Efficient Baselines**
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* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Flepp_Real-World_Mobile_Image_Denoising_Dataset_with_Efficient_Baselines_CVPR_2024_paper.html
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* Code:
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**SeNM-VAE: Semi-Supervised Noise Modeling with Hierarchical Variational Autoencoder**
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* Paper: https://arxiv.org/abs/2403.17502
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* Code: https://github.com/zhengdharia/SeNM-VAE
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**Transfer CLIP for Generalizable Image Denoising**
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* Paper: https://arxiv.org/abs/2403.15132
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* Code:
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**Unmixing Diffusion for Self-Supervised Hyperspectral Image Denoising**
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* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Zeng_Unmixing_Diffusion_for_Self-Supervised_Hyperspectral_Image_Denoising_CVPR_2024_paper.html
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* Code:
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**ZERO-IG: Zero-Shot Illumination-Guided Joint Denoising and Adaptive Enhancement for Low-Light Images**
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* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Shi_ZERO-IG_Zero-Shot_Illumination-Guided_Joint_Denoising_and_Adaptive_Enhancement_for_Low-Light_CVPR_2024_paper.html
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* Code: https://github.com/Doyle59217/ZeroIG
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## 6.图像恢复(Image Restoration)
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**Adapt or Perish: Adaptive Sparse Transformer with Attentive Feature Refinement for Image Restoration**
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* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Zhou_Adapt_or_Perish_Adaptive_Sparse_Transformer_with_Attentive_Feature_Refinement_CVPR_2024_paper.html
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* Code: https://github.com/joshyZhou/AST
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**Boosting Image Restoration via Priors from Pre-trained Models**
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* Paper: https://arxiv.org/abs/2403.06793
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* Code:
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**CoDe: An Explicit Content Decoupling Framework for Image Restoration**
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* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Gu_CoDe_An_Explicit_Content_Decoupling_Framework_for_Image_Restoration_CVPR_2024_paper.html
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* Code:
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**Deep Equilibrium Diffusion Restoration with Parallel Sampling**
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* Paper: https://arxiv.org/abs/2311.11600
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* Code: https://github.com/caojiezhang/DeqIR
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**Diff-Plugin: Revitalizing Details for Diffusion-based Low-level Tasks**
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* Paper: https://arxiv.org/abs/2403.00644
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* Code: https://github.com/yuhaoliu7456/Diff-Plugin
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**Distilling Semantic Priors from SAM to Efficient Image Restoration Models**
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* Paper: https://arxiv.org/abs/2403.16368
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* Code:
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**DocRes: A Generalist Model Toward Unifying Document Image Restoration Tasks**
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* Paper: https://arxiv.org/abs/2405.04408
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* Code: https://github.com/ZZZHANG-jx/DocRes
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**HIR-Diff: Unsupervised Hyperspectral Image Restoration Via Improved Diffusion Models**
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* Paper: https://arxiv.org/abs/2402.15865
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* Code: https://github.com/LiPang/HIRDiff
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**Image Restoration by Denoising Diffusion Models With Iteratively Preconditioned Guidance**
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* Paper: https://arxiv.org/abs/2312.16519
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* Code: https://github.com/tirer-lab/DDPG
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**Improving Image Restoration through Removing Degradations in Textual Representations**
|
||
* Paper: https://arxiv.org/abs/2312.17334
|
||
* Code: https://github.com/mrluin/TextualDegRemoval
|
||
|
||
**Learning Degradation-unaware Representation with Prior-based Latent Transformations for Blind Face Restoration**
|
||
* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Xie_Learning_Degradation-unaware_Representation_with_Prior-based_Latent_Transformations_for_Blind_Face_CVPR_2024_paper.html
|
||
* Code:
|
||
|
||
**Learning Diffusion Texture Priors for Image Restoration**
|
||
* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Ye_Learning_Diffusion_Texture_Priors_for_Image_Restoration_CVPR_2024_paper.html
|
||
* Code:
|
||
|
||
**Look-Up Table Compression for Efficient Image Restoration**
|
||
* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Li_Look-Up_Table_Compression_for_Efficient_Image_Restoration_CVPR_2024_paper.html
|
||
* Code:
|
||
|
||
**Multimodal Prompt Perceiver: Empower Adaptiveness, Generalizability and Fidelity for All-in-One Image Restoration**
|
||
* Paper: https://arxiv.org/abs/2312.02918
|
||
* Code:
|
||
|
||
**PFStorer: Personalized Face Restoration and Super-Resolution**
|
||
* Paper: https://arxiv.org/abs/2403.08436
|
||
* Code:
|
||
|
||
**Restoration by Generation with Constrained Priors**
|
||
* Paper: https://arxiv.org/abs/2312.17161
|
||
* Code:
|
||
|
||
**Scaling Up to Excellence: Practicing Model Scaling for Photo-Realistic Image Restoration In the Wild**
|
||
* Paper: https://arxiv.org/abs/2401.13627
|
||
* Code: https://github.com/Fanghua-Yu/SUPIR
|
||
|
||
**Selective Hourglass Mapping for Universal Image Restoration Based on Diffusion Model**
|
||
* Paper: https://arxiv.org/abs/2403.11157
|
||
* Code: https://github.com/iSEE-Laboratory/DiffUIR
|
||
|
||
**Turb-Seg-Res: A Segment-then-Restore Pipeline for Dynamic Videos with Atmospheric Turbulence**
|
||
* Paper: https://arxiv.org/abs/2404.13605
|
||
Code: https://github.com/Riponcs/Turb-Seg-Res
|
||
|
||
**WaveFace: Authentic Face Restoration with Efficient Frequency Recovery**
|
||
* Paper: https://arxiv.org/abs/2403.12760
|
||
* Code:
|
||
|
||
**Wavelet-based Fourier Information Interaction with Frequency Diffusion Adjustment for Underwater Image Restoration**
|
||
* Paper: https://arxiv.org/abs/2311.16845
|
||
* Code: https://github.com/zhihefang/wf-diff
|
||
|
||
## 7.图像增强(Image Enhancement)
|
||
**Color Shift Estimation-and-Correction for Image Enhancement**
|
||
* Paper: https://drive.google.com/file/d/1jZB2rW_I2WLTE5yNA4IZq9wb5p4NNOCR/view
|
||
* Code: https://github.com/yiyulics/CSEC
|
||
|
||
**Empowering Resampling Operation for Ultra-High-Definition Image Enhancement with Model-Aware Guidance**
|
||
* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Yu_Empowering_Resampling_Operation_for_Ultra-High-Definition_Image_Enhancement_with_Model-Aware_Guidance_CVPR_2024_paper.html
|
||
* Code: https://github.com/YPatrickW/LMAR
|
||
|
||
**Fourier Priors-Guided Diffusion for Zero-Shot Joint Low-Light Enhancement and Deblurring**
|
||
* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Lv_Fourier_Priors-Guided_Diffusion_for_Zero-Shot_Joint_Low-Light_Enhancement_and_Deblurring_CVPR_2024_paper.html
|
||
* Code:
|
||
|
||
**FlowIE：Efficient Image Enhancement via Rectified Flow**
|
||
* Paper: https://arxiv.org/abs/2406.00508
|
||
* Code: https://github.com/EternalEvan/FlowIE
|
||
|
||
**Light the Night: A Multi-Condition Diffusion Framework for Unpaired Low-Light Enhancement in Autonomous Driving**
|
||
* Paper: https://arxiv.org/abs/2404.04804
|
||
* Code: https://github.com/jinlong17/LightDiff
|
||
|
||
**Robust Depth Enhancement via Polarization Prompt Fusion Tuning**
|
||
* Paper: https://arxiv.org/abs/2404.04318
|
||
* Code: https://github.com/lastbasket/Polarization-Prompt-Fusion-Tuning
|
||
|
||
**Specularity Factorization for Low Light Enhancement**
|
||
* Paper: https://arxiv.org/abs/2404.01998
|
||
* Code:
|
||
|
||
**Towards Robust Event-guided Low-Light Image Enhancement: A Large-Scale Real-World Event-Image Dataset and Novel Approach**
|
||
* Paper: https://arxiv.org/abs/2404.00834
|
||
* Code: https://github.com/EthanLiang99/EvLight
|
||
|
||
**ZERO-IG: Zero-Shot Illumination-Guided Joint Denoising and Adaptive Enhancement for Low-Light Images**
|
||
* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Shi_ZERO-IG_Zero-Shot_Illumination-Guided_Joint_Denoising_and_Adaptive_Enhancement_for_Low-Light_CVPR_2024_paper.html
|
||
* Code: https://github.com/Doyle59217/ZeroIG
|
||
|
||
**Zero-Reference Low-Light Enhancement via Physical Quadruple Priors**
|
||
* Paper: https://arxiv.org/abs/2403.12933
|
||
* Code: https://github.com/daooshee/QuadPrior
|
||
|
||
### Video Enhancement
|
||
**Binarized Low-light Raw Video Enhancement**
|
||
* Paper: https://arxiv.org/abs/2403.19944
|
||
* Code: https://github.com/zhanggengchen/BRVE
|
||
|
||
**UVEB: A Large-scale Benchmark and Baseline Towards Real-World Underwater Video Enhancement**
|
||
* Paper: https://arxiv.org/abs/2404.14542
|
||
* Code: https://github.com/yzbouc/UVEB
|
||
|
||
## 8.图像修复(Inpainting)
|
||
**Amodal Completion via Progressive Mixed Context Diffusion**
|
||
* Paper: https://arxiv.org/abs/2312.15540
|
||
* Code: https://github.com/k8xu/amodal
|
||
|
||
**Brush2Prompt: Contextual Prompt Generator for Object Inpainting**
|
||
* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Chiu_Brush2Prompt_Contextual_Prompt_Generator_for_Object_Inpainting_CVPR_2024_paper.html
|
||
* Code:
|
||
|
||
**Don’t Look into the Dark: Latent Codes for Pluralistic Image Inpainting**
|
||
* Paper: https://arxiv.org/abs/2403.18186
|
||
* Code:
|
||
|
||
**Structure Matters: Tackling the Semantic Discrepancy in Diffusion Models for Image Inpainting**
|
||
* Paper: https://arxiv.org/abs/2403.19898
|
||
* Code: https://github.com/htyjers/StrDiffusion
|
||
|
||
### Video Inpainting
|
||
**AVID: Any-Length Video Inpainting with Diffusion Model**
|
||
* Paper: https://arxiv.org/abs/2312.03816
|
||
* Code: https://github.com/zhang-zx/AVID
|
||
|
||
**Towards Language-Driven Video Inpainting via Multimodal Large Language Models**
|
||
* Paper: https://arxiv.org/abs/2401.10226
|
||
* Code: https://github.com/jianzongwu/Language-Driven-Video-Inpainting
|
||
|
||
## 9.高动态范围成像(HDR Imaging)
|
||
**CLIPtone: Unsupervised Learning for Text-based Image Tone Adjustment**
|
||
* Paper: https://arxiv.org/abs/2404.01123
|
||
* Code: https://github.com/hmin970922/CLIPtone/
|
||
|
||
**Deep Video Inverse Tone Mapping Based on Temporal Clues**
|
||
* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Ye_Deep_Video_Inverse_Tone_Mapping_Based_on_Temporal_Clues_CVPR_2024_paper.html
|
||
* Code: https://github.com/ye3why/VITM-TC
|
||
|
||
**Generating Content for HDR Deghosting from Frequency View**
|
||
* Paper: https://arxiv.org/abs/2404.00849
|
||
* Code:
|
||
|
||
**HDRFlow: Real-Time HDR Video Reconstruction with Large Motions**
|
||
* Paper: https://arxiv.org/abs/2403.03447
|
||
* Code: https://github.com/OpenImagingLab/HDRFlow
|
||
|
||
**Perceptual Assessment and Optimization of HDR Image Rendering**
|
||
* Paper: https://arxiv.org/abs/2310.12877v4
|
||
* Code: https://github.com/cpb68/HDRQA/
|
||
|
||
**Towards HDR and HFR Video from Rolling-Mixed-Bit Spikings**
|
||
* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Chang_Towards_HDR_and_HFR_Video_from_Rolling-Mixed-Bit_Spikings_CVPR_2024_paper.html
|
||
* Code:
|
||
|
||
**Towards Real-World HDR Video Reconstruction: A Large-Scale Benchmark Dataset and A Two-Stage Alignment Network**
|
||
* Paper: https://arxiv.org/abs/2405.00244
|
||
* Code: https://github.com/yungsyu99/Real-HDRV
|
||
|
||
**Zero-Shot Structure-Preserving Diffusion Model for High Dynamic Range Tone Mapping**
|
||
* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Zhu_Zero-Shot_Structure-Preserving_Diffusion_Model_for_High_Dynamic_Range_Tone_Mapping_CVPR_2024_paper.html
|
||
* Code:
|
||
|
||
## 10.图像质量评价(Image Quality Assessment)
|
||
**Blind Image Quality Assessment Based on Geometric Order Learning**
|
||
* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Shin_Blind_Image_Quality_Assessment_Based_on_Geometric_Order_Learning_CVPR_2024_paper.html
|
||
* Code: https://github.com/nhshin-mcl/QCN
|
||
|
||
**Boosting Image Quality Assessment through Efficient Transformer Adaptation with Local Feature Enhancement**
|
||
* Paper: https://arxiv.org/abs/2308.12001
|
||
* Code:
|
||
|
||
**Bridging the Synthetic-to-Authentic Gap: Distortion-Guided Unsupervised Domain Adaptation for Blind Image Quality Assessment**
|
||
* Paper: https://arxiv.org/abs/2405.04167
|
||
* Code:
|
||
|
||
**CLIB-FIQA: Face Image Quality Assessment with Confidence Calibration**
|
||
* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Ou_CLIB-FIQA_Face_Image_Quality_Assessment_with_Confidence_Calibration_CVPR_2024_paper.html
|
||
* Code:
|
||
|
||
**Contrastive Pre-Training with Multi-View Fusion for No-Reference Point Cloud Quality Assessment**
|
||
* Paper: https://arxiv.org/abs/2403.10066
|
||
* Code:
|
||
|
||
**Deep Generative Model based Rate-Distortion for Image Downscaling Assessment**
|
||
* Paper: https://arxiv.org/abs/2403.15139
|
||
* Code: https://github.com/Byronliang8/IDA-RD
|
||
|
||
**Defense Against Adversarial Attacks on No-Reference Image Quality Models with Gradient Norm Regularization**
|
||
* Paper: https://arxiv.org/abs/2403.11397
|
||
* Code: https://github.com/YangiD/DefenseIQA-NT
|
||
|
||
**DSL-FIQA: Assessing Facial Image Quality via Dual-Set Degradation Learning and Landmark-Guided Transformer**
|
||
* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Chen_DSL-FIQA_Assessing_Facial_Image_Quality_via_Dual-Set_Degradation_Learning_and_CVPR_2024_paper.html
|
||
* Code:
|
||
|
||
**EvalCrafter: Benchmarking and Evaluating Large Video Generation Models**
|
||
* Paper: https://arxiv.org/abs/2310.11440
|
||
* Code: https://github.com/evalcrafter/EvalCrafter
|
||
|
||
**FineParser: A Fine-grained Spatio-temporal Action Parser for Human-centric Action Quality Assessment**
|
||
* Paper: https://arxiv.org/abs/2405.06887
|
||
* Code: https://github.com/PKU-ICST-MIPL/FineParser_CVPR2024
|
||
|
||
**KVQ: Kwai Video Quality Assessment for Short-form Videos**
|
||
* Paper: https://arxiv.org/abs/2402.07220
|
||
* Code: https://github.com/lixinustc/KVQ-Challenge-CVPR-NTIRE2024
|
||
|
||
**Learned Scanpaths Aid Blind Panoramic Video Quality Assessment**
|
||
* Paper: https://arxiv.org/abs/2404.00252
|
||
* Code: https://github.com/kalofan/AutoScanpathQA
|
||
|
||
**Modular Blind Video Quality Assessment**
|
||
* Paper: https://arxiv.org/abs/2402.19276
|
||
* Code: https://github.com/winwinwenwen77/ModularBVQA
|
||
|
||
**On the Content Bias in Fréchet Video Distance**
|
||
* Paper: https://arxiv.org/abs/2404.12391
|
||
* Code: https://github.com/songweige/content-debiased-fvd
|
||
|
||
**PTM-VQA: Efficient Video Quality Assessment Leveraging Diverse PreTrained Models from the Wild**
|
||
* Paper: https://arxiv.org/abs/2405.17765
|
||
* Code:
|
||
|
||
**Q-Instruct: Improving Low-level Visual Abilities for Multi-modality Foundation Models**
|
||
* Paper: https://arxiv.org/abs/2311.06783
|
||
* Code: https://github.com/Q-Future/Q-Instruct
|
||
|
||
## 11.插帧(Frame Interpolation)
|
||
**Data-Efficient Unsupervised Interpolation Without Any Intermediate Frame for 4D Medical Images**
|
||
Paper: https://arxiv.org/abs/2404.01464
|
||
Code: https://github.com/jungeun122333/UVI-Net
|
||
|
||
**IQ-VFI: Implicit Quadratic Motion Estimation for Video Frame Interpolation**
|
||
* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Hu_IQ-VFI_Implicit_Quadratic_Motion_Estimation_for_Video_Frame_Interpolation_CVPR_2024_paper.html
|
||
* Code:
|
||
|
||
**Perceptual-Oriented Video Frame Interpolation Via Asymmetric Synergistic Blending**
|
||
* Paper: https://arxiv.org/abs/2404.06692
|
||
* Code:
|
||
|
||
**Sparse Global Matching for Video Frame Interpolation with Large Motion**
|
||
* Paper: https://arxiv.org/abs/2404.06913
|
||
* Code: https://github.com/MCG-NJU/SGM-VFI
|
||
|
||
**SportsSloMo: A New Benchmark and Baselines for Human-centric Video Frame Interpolation**
|
||
* Paper: https://arxiv.org/abs/2308.16876
|
||
* Code: https://github.com/neu-vi/SportsSloMo
|
||
|
||
**TTA-EVF: Test-Time Adaptation for Event-based Video Frame Interpolation via Reliable Pixel and Sample Estimation**
|
||
* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Cho_TTA-EVF_Test-Time_Adaptation_for_Event-based_Video_Frame_Interpolation_via_Reliable_CVPR_2024_paper.html
|
||
* Code: https://github.com/Chohoonhee/TTA-EVF
|
||
|
||
**Video Frame Interpolation via Direct Synthesis with the Event-based Reference**
|
||
* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Liu_Video_Frame_Interpolation_via_Direct_Synthesis_with_the_Event-based_Reference_CVPR_2024_paper.html
|
||
* Code:
|
||
|
||
**Video Interpolation with Diffusion Models**
|
||
* Paper: https://arxiv.org/abs/2404.01203
|
||
* Code:
|
||
|
||
## 12.视频/图像压缩(Video/Image Compression)
|
||
**C3: High-performance and low-complexity neural compression from a single image or video**
|
||
* Paper: https://arxiv.org/abs/2312.02753
|
||
* Code: https://github.com/google-deepmind/c3_neural_compression
|
||
|
||
**Generative Latent Coding for Ultra-Low Bitrate Image Compression**
|
||
* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Jia_Generative_Latent_Coding_for_Ultra-Low_Bitrate_Image_Compression_CVPR_2024_paper.html
|
||
* Code:
|
||
|
||
**Laplacian-guided Entropy Model in Neural Codec with Blur-dissipated Synthesis**
|
||
* Paper: https://arxiv.org/abs/2403.16258
|
||
* Code:
|
||
|
||
**Learned Lossless Image Compression based on Bit Plane Slicing**
|
||
* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Zhang_Learned_Lossless_Image_Compression_based_on_Bit_Plane_Slicing_CVPR_2024_paper.html
|
||
* Code: https://github.com/ZZ022/ArIB-BPS
|
||
|
||
**Towards Backward-Compatible Continual Learning of Image Compression**
|
||
* Paper: https://arxiv.org/abs/2402.18862
|
||
* Code: https://gitlab.com/viper-purdue/continual-compression
|
||
|
||
### Video Compression
|
||
**Task-Aware Encoder Control for Deep Video Compression**
|
||
* Paper: https://arxiv.org/abs/2404.04848
|
||
* Code:
|
||
|
||
**Low-Latency Neural Stereo Streaming**
|
||
* Paper: https://arxiv.org/abs/2403.17879
|
||
* Code:
|
||
|
||
**Neural Video Compression with Feature Modulation**
|
||
* Paper: https://arxiv.org/abs/2402.17414
|
||
* Code: https://github.com/microsoft/DCVC
|
||
|
||
## 13.压缩图像质量增强(Compressed Image Quality Enhancement)
|
||
**CPGA: Coding Priors-Guided Aggregation Network for Compressed Video Quality Enhancement**
|
||
* Paper: https://arxiv.org/abs/2403.10362
|
||
* Code:
|
||
|
||
**Enhancing Quality of Compressed Images by Mitigating Enhancement Bias Towards Compression Domain**
|
||
* Paper: https://arxiv.org/abs/2402.17200
|
||
* Code:
|
||
|
||
## 14.图像去反光(Image Reflection Removal)
|
||
**Language-guided Image Reflection Separation**
|
||
* Paper: https://arxiv.org/abs/2402.11874
|
||
* Code:
|
||
|
||
**Revisiting Singlelmage Reflection Removal in the Wild**
|
||
* Paper: https://arxiv.org/abs/2311.17320
|
||
* Code: https://github.com/zhuyr97/Reflection_RemoVal_CVPR2024
|
||
|
||
## 15.图像去阴影(Image Shadow Removal)
|
||
**HomoFormer: Homogenized Transformer for Image Shadow Removal**
|
||
* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Xiao_HomoFormer_Homogenized_Transformer_for_Image_Shadow_Removal_CVPR_2024_paper.html
|
||
* Code: https://github.com/jiexiaou/HomoFormer
|
||
|
||
## 16.图像上色(Image Colorization)
|
||
**Automatic Controllable Colorization by Imagination**
|
||
* Paper: https://arxiv.org/abs/2404.05661
|
||
* Code: https://github.com/xy-cong/imagine-colorization
|
||
|
||
**Generative Quanta Color Imaging**
|
||
* Paper: https://arxiv.org/abs/2403.19066
|
||
* Code:
|
||
|
||
**Learning Inclusion Matching for Animation Paint Bucket Colorization**
|
||
* Paper: https://arxiv.org/abs/2403.18342
|
||
* Code: https://github.com/ykdai/BasicPBC
|
||
|
||
## 17.图像和谐化(Image Harmonization)
|
||
**Relightful Harmonization: Lighting-aware Portrait Background Replacement**
|
||
* Paper: https://arxiv.org/abs/2312.06886
|
||
* Code:
|
||
|
||
**Video Harmonization with Triplet Spatio-Temporal Variation Patterns**
|
||
* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Guo_Video_Harmonization_with_Triplet_Spatio-Temporal_Variation_Patterns_CVPR_2024_paper.html
|
||
* Code: https://github.com/zhenglab/VideoTripletTransformer
|
||
## 18.视频稳相(Video Stabilization)
|
||
**3D Multi-frame Fusion for Video Stabilization**
|
||
* Paper: https://arxiv.org/abs/2404.12887
|
||
* Code:
|
||
|
||
**Harnessing Meta-Learning for Improving Full-Frame Video Stabilization**
|
||
* Paper: https://arxiv.org/abs/2403.03662
|
||
* Code: https://github.com/MKashifAli/MetaVideoStab
|
||
|
||
## 19.图像融合(Image Fusion)
|
||
**Equivariant Multi-Modality Image Fusion**
|
||
* Paper： https://arxiv.org/abs/2305.11443
|
||
* Code: https://github.com/Zhaozixiang1228/MMIF-EMMA
|
||
|
||
**MRFS: Mutually Reinforcing Image Fusion and Segmentation**
|
||
* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Zhang_MRFS_Mutually_Reinforcing_Image_Fusion_and_Segmentation_CVPR_2024_paper.html
|
||
* Code: https://github.com/HaoZhang1018/MRFS
|
||
|
||
**Neural Spline Fields for Burst Image Fusion and Layer Separation**
|
||
* Paper: https://arxiv.org/abs/2312.14235
|
||
* Code: https://github.com/princeton-computational-imaging/NSF
|
||
|
||
**Probing Synergistic High-Order Interaction in Infrared and Visible Image Fusion**
|
||
* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Zheng_Probing_Synergistic_High-Order_Interaction_in_Infrared_and_Visible_Image_Fusion_CVPR_2024_paper.html
|
||
* Code:
|
||
|
||
**Revisiting Spatial-Frequency Information Integration from a Hierarchical Perspective for Panchromatic and Multi-Spectral Image Fusion**
|
||
* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Zheng_Probing_Synergistic_High-Order_Interaction_in_Infrared_and_Visible_Image_Fusion_CVPR_2024_paper.html
|
||
* Code:
|
||
|
||
**Text-IF: Leveraging Semantic Text Guidance for Degradation-Aware and Interactive Image Fusion**
|
||
* Paper: https://arxiv.org/abs/2403.16387
|
||
* Code: https://github.com/XunpengYi/Text-IF
|
||
|
||
**Task-Customized Mixture of Adapters for General Image Fusion**
|
||
* Paper: https://arxiv.org/abs/2403.12494
|
||
* Code: https://github.com/YangSun22/TC-MoA
|
||
|
||
## 20.其他任务(Others)
|
||
**Close Imitation of Expert Retouching for Black-and-White Photography**
|
||
* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Shin_Close_Imitation_of_Expert_Retouching_for_Black-and-White_Photography_CVPR_2024_paper.html
|
||
* Code: https://github.com/seunghyuns98/Decolorization
|
||
|
||
**Content-Adaptive Non-Local Convolution for Remote Sensing Pansharpening**
|
||
Paper: https://arxiv.org/abs/2404.07543
|
||
Code: https://github.com/Duanyll/CANConv
|
||
|
||
**DiffSCI: Zero-Shot Snapshot Compressive Imaging via Iterative Spectral Diffusion Model**
|
||
* Paper: https://arxiv.org/abs/2311.11417
|
||
* Code: https://github.com/PAN083/DiffSCI
|
||
|
||
**Dual Prior Unfolding for Snapshot Compressive Imaging**
|
||
* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Zhang_Dual_Prior_Unfolding_for_Snapshot_Compressive_Imaging_CVPR_2024_paper.html
|
||
* Code: https://github.com/ZhangJC-2k/DPU
|
||
|
||
**Dual-Camera Smooth Zoom on Mobile Phones**
|
||
* Paper: https://arxiv.org/abs/2404.04908
|
||
* Code: https://github.com/ZcsrenlongZ/ZoomGS
|
||
|
||
**Dual-scale Transformer for Large-scale Single-Pixel Imaging**
|
||
* Paper: https://arxiv.org/abs/2404.05001
|
||
* Code: https://github.com/Gang-Qu/HATNet-SPI
|
||
|
||
**Genuine Knowledge from Practice: Diffusion Test-Time Adaptation for Video Adverse Weather Removal**
|
||
* Paper: https://arxiv.org/abs/2403.07684
|
||
* Code: https://github.com/scott-yjyang/DiffTTA
|
||
|
||
**Language-driven All-in-one Adverse Weather Removal**
|
||
* Paper: https://arxiv.org/abs/2312.01381
|
||
* Code:
|
||
|
||
**Learning to Remove Wrinkled Transparent Film with Polarized Prior**
|
||
* Paper: https://arxiv.org/abs/2403.04368
|
||
* Code: https://github.com/jqtangust/FilmRemovalww
|
||
|
||
**Misalignment-Robust Frequency Distribution Loss for Image Transformation**
|
||
* Paper: https://arxiv.org/abs/2402.18192
|
||
* Code: https://github.com/eezkni/FDL
|
||
|
||
**On the Robustness of Language Guidance for Low-Level Vision Tasks: Findings from Depth Estimation**
|
||
* Paper: https://arxiv.org/abs/2404.08540
|
||
* Code: https://github.com/agneet42/lang_depth
|
||
|
||
**ParamISP: Learned Forward and Inverse ISPs using Camera Parameters**
|
||
* Paper: https://arxiv.org/abs/2312.13313
|
||
* Code: https://github.com/woo525/ParamISP
|
||
|
||
**RecDiffusion: Rectangling for Image Stitching with Diffusion Models**
|
||
* Paper: https://arxiv.org/abs/2402.18192
|
||
* Code: https://github.com/lhaippp/RecDiffusion
|
||
|
||
**Residual Denoising Diffusion Models**
|
||
* Paper: https://arxiv.org/abs/2308.13712
|
||
* Code: https://github.com/nachifur/RDDM
|
||
|
||
**Real-Time Exposure Correction via Collaborative Transformations and Adaptive Sampling**
|
||
* Paper: https://arxiv.org/abs/2404.11884
|
||
* Code: https://github.com/HUST-IAL/CoTF
|
||
|
||
**SCINeRF: Neural Radiance Fields from a Snapshot Compressive Image**
|
||
* Paper: https://arxiv.org/abs/2403.20018
|
||
* Code: https://github.com/WU-CVGL/SCINeRF
|
||
|
||
**Seeing Motion at Nighttime with an Event Camera**
|
||
* Paper: https://arxiv.org/abs/2404.11884
|
||
* Code: https://github.com/Liu-haoyue/NER-Net
|
||
|
||
**Shadow Generation for Composite Image Using Diffusion Model**
|
||
* Paper: https://arxiv.org/abs/2403.15234
|
||
* Code: https://github.com/bcmi/Object-Shadow-Generation-Dataset-DESOBAv2
|
||
|
||
**Improving Spectral Snapshot Reconstruction with Spectral-Spatial Rectification**
|
||
* Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Zhang_Improving_Spectral_Snapshot_Reconstruction_with_Spectral-Spatial_Rectification_CVPR_2024_paper.html
|
||
* Code: https://github.com/ZhangJC-2k/SSR
|
||
|
||
## 参考
|
||
相关Low-Level-Vision整理
|
||
Awesome-CVPR2020-Low-Level-Vision
|
||
Awesome-ECCV2020-Low-Level-Vision
|
||
Awesome-Low-Level-Vision-Research-Groups
|
||
Awesome-AIGC-Research-Groups
|