CVPR2024|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】
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CVPR2024|底层视觉相关论文汇总(如果觉得有帮助,欢迎点赞和收藏)
- Awesome-CVPR2024-Low-Level-Vision[](https://github.com/sindresorhus/awesome)
- 1.超分辨率(Super-Resolution)
- AdaBM: On-the-Fly Adaptive Bit Mapping for Image Super-Resolution
- A Dynamic Kernel Prior Model for Unsupervised Blind Image Super-Resolution
- APISR: Anime Production Inspired Real-World Anime Super-Resolution
- Arbitrary-Scale Image Generation and Upsampling using Latent Diffusion Model and Implicit Neural Decoder
- Beyond Image Super-Resolution for Image Recognition with Task-Driven Perceptual Loss
- Bilateral Event Mining and Complementary for Event Stream Super-Resolution
- Boosting Flow-based Generative Super-Resolution Models via Learned Prior
- Building Bridges across Spatial and Temporal Resolutions: Reference-Based Super-Resolution via Change Priors and Conditional Diffusion Model
- CAMixerSR: Only Details Need More “Attention”
- CFAT: Unleashing Triangular Windows for Image Super-resolution
- Continuous Optical Zooming: A Benchmark for Arbitrary-Scale Image Super-Resolution in Real World
- CoSeR: Bridging Image and Language for Cognitive Super-Resolution
- CDFormer: When Degradation Prediction Embraces Diffusion Model for Blind Image Super-Resolution
- CycleINR: Cycle Implicit Neural Representation for Arbitrary-Scale Volumetric Super-Resolution of Medical Data
- Diffusion-based Blind Text Image Super-Resolution
- DiSR-NeRF: Diffusion-Guided View-Consistent Super-Resolution NeRF
- Image Processing GNN: Breaking Rigidity in Super-Resolution
- Latent Modulated Function for Computational Optimal Continuous Image Representation
- Learning Coupled Dictionaries from Unpaired Data for Image Super-Resolution
- Learning Large-Factor EM Image Super-Resolution with Generative Priors
- Low-Res Leads the Way: Improving Generalization for Super-Resolution by Self-Supervised Learning
- Navigating Beyond Dropout: An Intriguing Solution towards Generalizable Image Super-Resolution
- Neural Super-Resolution for Real-time Rendering with Radiance Demodulation
- Rethinking Diffusion Model for Multi-Contrast MRI Super-Resolution
- SeD: Semantic-Aware Discriminator for Image Super-Resolution
- SeeSR: Towards Semantics-Aware Real-World Image Super-Resolution
- Self-Adaptive Reality-Guided Diffusion for Artifact-Free Super-Resolution
- SinSR: Diffusion-Based Image Super-Resolution in a Single Step
- Super-Resolution Reconstruction from Bayer-Pattern Spike Streams
- Text-guided Explorable Image Super-resolution
- Training Generative Image Super-Resolution Models by Wavelet-Domain Losses Enables Better Control of Artifacts
- Transcending the Limit of Local Window: Advanced Super-Resolution Transformer with Adaptive Token Dictionary
- Uncertainty-Aware Source-Free Adaptive Image Super-Resolution with Wavelet Augmentation Transformer
- Universal Robustness via Median Randomized Smoothing for Real-World Super-Resolution
- Video Super-Resolution
- Enhancing Video Super-Resolution via Implicit Resampling-based Alignment
- FMA-Net: Flow-Guided Dynamic Filtering and Iterative Feature Refinement with Multi-Attention for Joint Video Super-Resolution and Deblurring
- Learning Spatial Adaptation and Temporal Coherence in Diffusion Models for Video Super-Resolution
- Upscale-A-Video: Temporal-Consistent Diffusion Model for Real-World Video Super-Resolution
- Video Super-Resolution Transformer with Masked Inter&Intra-Frame Attention
- 2.图像去雨(Image Deraining)
- 3.图像去雾(Image Dehazing)
- 4.去模糊(Deblurring)
- A Unified Framework for Microscopy Defocus Deblur with Multi-Pyramid Transformer and Contrastive Learning
- AdaRevD: Adaptive Patch Exiting Reversible Decoder Pushes the Limit of Image Deblurring
- Blur2Blur: Blur Conversion for Unsupervised Image Deblurring on Unknown Domains
- Fourier Priors-Guided Diffusion for Zero-Shot Joint Low-Light Enhancement and Deblurring
- ID-Blau: Image Deblurring by Implicit Diffusion-based reBLurring AUgmentation
- LDP: Language-driven Dual-Pixel Image Defocus Deblurring Network
- Mitigating Motion Blur in Neural Radiance Fields with Events and Frames
- Motion-adaptive Separable Collaborative Filters for Blind Motion Deblurring
- Motion Blur Decomposition with Cross-shutter Guidance
- Real-World Efficient Blind Motion Deblurring via Blur Pixel Discretization
- Spike-guided Motion Deblurring with Unknown Modal Spatiotemporal Alignment
- Unsupervised Blind Image Deblurring Based on Self-Enhancement
- Video Deblurring
- Blur-aware Spatio-temporal Sparse Transformer for Video Deblurring
- EVS-assisted Joint Deblurring Rolling-Shutter Correction and Video Frame Interpolation through Sensor Inverse Modeling
- Frequency-aware Event-based Video Deblurring for Real-World Motion Blur
- Latency Correction for Event-guided Deblurring and Frame Interpolation
- 5.去噪(Denoising)
- LAN: Learning to Adapt Noise for Image Denoising
- LED: A Large-scale Real-world Paired Dataset for Event Camera Denoising
- Robust Image Denoising through Adversarial Frequency Mixup
- Real-World Mobile Image Denoising Dataset with Efficient Baselines
- SeNM-VAE: Semi-Supervised Noise Modeling with Hierarchical Variational Autoencoder
- Transfer CLIP for Generalizable Image Denoising
- Unmixing Diffusion for Self-Supervised Hyperspectral Image Denoising
- ZERO-IG: Zero-Shot Illumination-Guided Joint Denoising and Adaptive Enhancement for Low-Light Images
- 6.图像恢复(Image Restoration)
- Adapt or Perish: Adaptive Sparse Transformer with Attentive Feature Refinement for Image Restoration
- Boosting Image Restoration via Priors from Pre-trained Models
- CoDe: An Explicit Content Decoupling Framework for Image Restoration
- Deep Equilibrium Diffusion Restoration with Parallel Sampling
- Diff-Plugin: Revitalizing Details for Diffusion-based Low-level Tasks
- Distilling Semantic Priors from SAM to Efficient Image Restoration Models
- DocRes: A Generalist Model Toward Unifying Document Image Restoration Tasks
- HIR-Diff: Unsupervised Hyperspectral Image Restoration Via Improved Diffusion Models
- Image Restoration by Denoising Diffusion Models With Iteratively Preconditioned Guidance
- Improving Image Restoration through Removing Degradations in Textual Representations
- Learning Degradation-unaware Representation with Prior-based Latent Transformations for Blind Face Restoration
- Learning Diffusion Texture Priors for Image Restoration
- Look-Up Table Compression for Efficient Image Restoration
- Multimodal Prompt Perceiver: Empower Adaptiveness, Generalizability and Fidelity for All-in-One Image Restoration
- PFStorer: Personalized Face Restoration and Super-Resolution
- Restoration by Generation with Constrained Priors
- Scaling Up to Excellence: Practicing Model Scaling for Photo-Realistic Image Restoration In the Wild
- Selective Hourglass Mapping for Universal Image Restoration Based on Diffusion Model
- Turb-Seg-Res: A Segment-then-Restore Pipeline for Dynamic Videos with Atmospheric Turbulence
- WaveFace: Authentic Face Restoration with Efficient Frequency Recovery
- Wavelet-based Fourier Information Interaction with Frequency Diffusion Adjustment for Underwater Image Restoration
- 7.图像增强(Image Enhancement)
- Color Shift Estimation-and-Correction for Image Enhancement
- Empowering Resampling Operation for Ultra-High-Definition Image Enhancement with Model-Aware Guidance
- Fourier Priors-Guided Diffusion for Zero-Shot Joint Low-Light Enhancement and Deblurring
- FlowIE:Efficient Image Enhancement via Rectified Flow
- Light the Night: A Multi-Condition Diffusion Framework for Unpaired Low-Light Enhancement in Autonomous Driving
- Robust Depth Enhancement via Polarization Prompt Fusion Tuning
- Specularity Factorization for Low Light Enhancement
- Towards Robust Event-guided Low-Light Image Enhancement: A Large-Scale Real-World Event-Image Dataset and Novel Approach
- ZERO-IG: Zero-Shot Illumination-Guided Joint Denoising and Adaptive Enhancement for Low-Light Images
- Zero-Reference Low-Light Enhancement via Physical Quadruple Priors
- Video Enhancement
- 8.图像修复(Inpainting)
- 9.高动态范围成像(HDR Imaging)
- CLIPtone: Unsupervised Learning for Text-based Image Tone Adjustment
- Deep Video Inverse Tone Mapping Based on Temporal Clues
- Generating Content for HDR Deghosting from Frequency View
- HDRFlow: Real-Time HDR Video Reconstruction with Large Motions
- Perceptual Assessment and Optimization of HDR Image Rendering
- Towards HDR and HFR Video from Rolling-Mixed-Bit Spikings
- Towards Real-World HDR Video Reconstruction: A Large-Scale Benchmark Dataset and A Two-Stage Alignment Network
- Zero-Shot Structure-Preserving Diffusion Model for High Dynamic Range Tone Mapping
- 10.图像质量评价(Image Quality Assessment)
- Blind Image Quality Assessment Based on Geometric Order Learning
- Boosting Image Quality Assessment through Efficient Transformer Adaptation with Local Feature Enhancement
- Bridging the Synthetic-to-Authentic Gap: Distortion-Guided Unsupervised Domain Adaptation for Blind Image Quality Assessment
- CLIB-FIQA: Face Image Quality Assessment with Confidence Calibration
- Contrastive Pre-Training with Multi-View Fusion for No-Reference Point Cloud Quality Assessment
- Deep Generative Model based Rate-Distortion for Image Downscaling Assessment
- Defense Against Adversarial Attacks on No-Reference Image Quality Models with Gradient Norm Regularization
- DSL-FIQA: Assessing Facial Image Quality via Dual-Set Degradation Learning and Landmark-Guided Transformer
- EvalCrafter: Benchmarking and Evaluating Large Video Generation Models
- FineParser: A Fine-grained Spatio-temporal Action Parser for Human-centric Action Quality Assessment
- KVQ: Kwai Video Quality Assessment for Short-form Videos
- Learned Scanpaths Aid Blind Panoramic Video Quality Assessment
- Modular Blind Video Quality Assessment
- On the Content Bias in Fréchet Video Distance
- PTM-VQA: Efficient Video Quality Assessment Leveraging Diverse PreTrained Models from the Wild
- Q-Instruct: Improving Low-level Visual Abilities for Multi-modality Foundation Models
- 11.插帧(Frame Interpolation)
- Data-Efficient Unsupervised Interpolation Without Any Intermediate Frame for 4D Medical Images
- IQ-VFI: Implicit Quadratic Motion Estimation for Video Frame Interpolation
- Perceptual-Oriented Video Frame Interpolation Via Asymmetric Synergistic Blending
- Sparse Global Matching for Video Frame Interpolation with Large Motion
- SportsSloMo: A New Benchmark and Baselines for Human-centric Video Frame Interpolation
- TTA-EVF: Test-Time Adaptation for Event-based Video Frame Interpolation via Reliable Pixel and Sample Estimation
- Video Frame Interpolation via Direct Synthesis with the Event-based Reference
- Video Interpolation with Diffusion Models
- 12.视频/图像压缩(Video/Image Compression)
- C3: High-performance and low-complexity neural compression from a single image or video
- Generative Latent Coding for Ultra-Low Bitrate Image Compression
- Laplacian-guided Entropy Model in Neural Codec with Blur-dissipated Synthesis
- Learned Lossless Image Compression based on Bit Plane Slicing
- Towards Backward-Compatible Continual Learning of Image Compression
- Video Compression
- 13.压缩图像质量增强(Compressed Image Quality Enhancement)
- 14.图像去反光(Image Reflection Removal)
- 15.图像去阴影(Image Shadow Removal)
- 16.图像上色(Image Colorization)
- 17.图像和谐化(Image Harmonization)
- 18.视频稳相(Video Stabilization)
- 19.图像融合(Image Fusion)
- Equivariant Multi-Modality Image Fusion
- MRFS: Mutually Reinforcing Image Fusion and Segmentation
- Neural Spline Fields for Burst Image Fusion and Layer Separation
- Probing Synergistic High-Order Interaction in Infrared and Visible Image Fusion
- Revisiting Spatial-Frequency Information Integration from a Hierarchical Perspective for Panchromatic and Multi-Spectral Image Fusion
- Text-IF: Leveraging Semantic Text Guidance for Degradation-Aware and Interactive Image Fusion
- Task-Customized Mixture of Adapters for General Image Fusion
- 20.其他任务(Others)
- Close Imitation of Expert Retouching for Black-and-White Photography
- Content-Adaptive Non-Local Convolution for Remote Sensing Pansharpening
- DiffSCI: Zero-Shot Snapshot Compressive Imaging via Iterative Spectral Diffusion Model
- Dual Prior Unfolding for Snapshot Compressive Imaging
- Dual-Camera Smooth Zoom on Mobile Phones
- Dual-scale Transformer for Large-scale Single-Pixel Imaging
- Genuine Knowledge from Practice: Diffusion Test-Time Adaptation for Video Adverse Weather Removal
- Language-driven All-in-one Adverse Weather Removal
- Learning to Remove Wrinkled Transparent Film with Polarized Prior
- Misalignment-Robust Frequency Distribution Loss for Image Transformation
- On the Robustness of Language Guidance for Low-Level Vision Tasks: Findings from Depth Estimation
- ParamISP: Learned Forward and Inverse ISPs using Camera Parameters
- RecDiffusion: Rectangling for Image Stitching with Diffusion Models
- Residual Denoising Diffusion Models
- Real-Time Exposure Correction via Collaborative Transformations and Adaptive Sampling
- SCINeRF: Neural Radiance Fields from a Snapshot Compressive Image
- Seeing Motion at Nighttime with an Event Camera
- Shadow Generation for Composite Image Using Diffusion Model
- Improving Spectral Snapshot Reconstruction with Spectral-Spatial Rectification
- 参考
- 相关Low-Level-Vision整理
Awesome-CVPR2024-Low-Level-Vision
整理汇总下今年CVPR底层视觉(Low-Level Vision)相关的论文和代码,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。
欢迎star,fork和PR~
优先在Github更新:Awesome-CVPR2024-Low-Level-Vision,欢迎star~
知乎:https://zhuanlan.zhihu.com/p/684196283
参考或转载请注明出处
CVPR2024官网:https://cvpr.thecvf.com/Conferences/2024
CVPR接收论文列表:https://cvpr.thecvf.com/Conferences/2024/AcceptedPapers
CVPR完整论文库:https://openaccess.thecvf.com/CVPR2024
开会时间:2024年6月17日-6月21日
论文接收公布时间:2024年2月27日
【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.图像修复(Inpainting)
- 9.高动态范围成像(HDR Imaging)
- 10.图像质量评价(Image Quality Assessment)
- 11.插帧(Frame Interpolation)
- 12.视频/图像压缩(Video/Image Compression)
- 13.压缩图像质量增强(Compressed Image Quality Enhancement)
- 14.图像去反光(Image Reflection Removal)
- 15.图像去阴影(Image Shadow Removal)
- 16.图像上色(Image Colorization)
- 17.图像和谐化(Image Harmonization)
- 18.视频稳相(Video Stabilization)
- 19.图像融合(Image Fusion)
- 20.其他任务(Others)
1.超分辨率(Super-Resolution)
AdaBM: On-the-Fly Adaptive Bit Mapping for Image Super-Resolution
- Paper: https://arxiv.org/abs/2404.03296
- Code: https://github.com/Cheeun/AdaBM
A Dynamic Kernel Prior Model for Unsupervised Blind Image Super-Resolution
- Paper: https://arxiv.org/abs/2404.15620
- Code: https://github.com/XYLGroup/DKP
APISR: Anime Production Inspired Real-World Anime Super-Resolution
- Paper: https://arxiv.org/abs/2403.01598
- Code: https://github.com/Kiteretsu77/APISR
Arbitrary-Scale Image Generation and Upsampling using Latent Diffusion Model and Implicit Neural Decoder
- Paper: https://arxiv.org/abs/2403.10255v1
- Code: https://github.com/zhenshij/arbitrary-scale-diffusion
Beyond Image Super-Resolution for Image Recognition with Task-Driven Perceptual Loss
- Paper: https://arxiv.org/abs/2404.01692
- Code: https://github.com/JaehaKim97/SR4IR
Bilateral Event Mining and Complementary for Event Stream Super-Resolution
- Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Huang_Bilateral_Event_Mining_and_Complementary_for_Event_Stream_Super-Resolution_CVPR_2024_paper.html
- Code: https://github.com/Lqm26/BMCNet-ESR
Boosting Flow-based Generative Super-Resolution Models via Learned Prior
- Paper: https://arxiv.org/abs/2403.10988
- Code: https://github.com/liyuantsao/FlowSR-LP
Building Bridges across Spatial and Temporal Resolutions: Reference-Based Super-Resolution via Change Priors and Conditional Diffusion Model
- Paper: https://arxiv.org/abs/2403.17460
- Code: https://github.com/dongrunmin/RefDiff
CAMixerSR: Only Details Need More “Attention”
- Paper: https://arxiv.org/abs/2402.19289
- Code: https://github.com/icandle/CAMixerSR
CFAT: Unleashing Triangular Windows for Image Super-resolution
- Paper: https://arxiv.org/abs/2403.16143
- Code: https://github.com/rayabhisek123/CFAT
Continuous Optical Zooming: A Benchmark for Arbitrary-Scale Image Super-Resolution in Real World
- 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
- Code: https://github.com/pf0607/COZ
CoSeR: Bridging Image and Language for Cognitive Super-Resolution
- Paper: https://arxiv.org/abs/2311.16512
- Code: https://github.com/VINHYU/CoSeR
CDFormer: When Degradation Prediction Embraces Diffusion Model for Blind Image Super-Resolution
- Paper: https://arxiv.org/abs/2405.07648
- Code: https://github.com/I2-Multimedia-Lab/CDFormer
CycleINR: Cycle Implicit Neural Representation for Arbitrary-Scale Volumetric Super-Resolution of Medical Data
- Paper: https://arxiv.org/abs/2404.04878
- Code:
Diffusion-based Blind Text Image Super-Resolution
- Paper: https://arxiv.org/abs/2312.08886
- Code: https://github.com/YuzheZhang-1999/DiffTSR
DiSR-NeRF: Diffusion-Guided View-Consistent Super-Resolution NeRF
- Paper: https://arxiv.org/abs/2404.00874
- Code:
Image Processing GNN: Breaking Rigidity in Super-Resolution
- Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Tian_Image_Processing_GNN_Breaking_Rigidity_in_Super-Resolution_CVPR_2024_paper.html
- Code: https://github.com/huawei-noah/Efficient-Computing/tree/master/LowLevel/IPG
Latent Modulated Function for Computational Optimal Continuous Image Representation
- Paper: https://arxiv.org/abs/2404.16451
- Code: https://github.com/HeZongyao/LMF
Learning Coupled Dictionaries from Unpaired Data for Image Super-Resolution
- Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Wang_Learning_Coupled_Dictionaries_from_Unpaired_Data_for_Image_Super-Resolution_CVPR_2024_paper.html
- Code:
Learning Large-Factor EM Image Super-Resolution with Generative Priors
- Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Shou_Learning_Large-Factor_EM_Image_Super-Resolution_with_Generative_Priors_CVPR_2024_paper.html
- Code: https://github.com/jtshou/GPEMSR
Low-Res Leads the Way: Improving Generalization for Super-Resolution by Self-Supervised Learning
- Paper: https://arxiv.org/abs/2403.02601
- Code: https://github.com/haoyuc/LWay
Navigating Beyond Dropout: An Intriguing Solution towards Generalizable Image Super-Resolution
- Paper: https://arxiv.org/abs/2402.18929v2
- Code: https://github.com/Dreamzz5/Simple-Align
Neural Super-Resolution for Real-time Rendering with Radiance Demodulation
- Paper: https://arxiv.org/abs/2308.06699
- Code: https://github.com/Riga2/NSRD
Rethinking Diffusion Model for Multi-Contrast MRI Super-Resolution
- Paper: https://arxiv.org/abs/2404.04785
- Code: https://github.com/GuangYuanKK/DiffMSR
SeD: Semantic-Aware Discriminator for Image Super-Resolution
- Paper: https://arxiv.org/abs/2402.19387
- Code: https://github.com/lbc12345/SeD
SeeSR: Towards Semantics-Aware Real-World Image Super-Resolution
- Paper: https://arxiv.org/abs/2311.16518
- Code: https://github.com/cswry/SeeSR
Self-Adaptive Reality-Guided Diffusion for Artifact-Free Super-Resolution
- Paper: https://arxiv.org/abs/2403.16643
- Code: https://github.com/ProAirVerse/Self-Adaptive-Guidance-Diffusion
SinSR: Diffusion-Based Image Super-Resolution in a Single Step
- Paper: https://github.com/wyf0912/SinSR/blob/main/main.pdf
- Code: https://github.com/wyf0912/SinSR
Super-Resolution Reconstruction from Bayer-Pattern Spike Streams
- Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Dong_Super-Resolution_Reconstruction_from_Bayer-Pattern_Spike_Streams_CVPR_2024_paper.html
- Code: https://github.com/csycdong/CSCSR
Text-guided Explorable Image Super-resolution
- Paper: https://arxiv.org/abs/2403.01124
- Code:
Training Generative Image Super-Resolution Models by Wavelet-Domain Losses Enables Better Control of Artifacts
- Paper: https://arxiv.org/abs/2402.19215
- Code: https://github.com/mandalinadagi/wgsr
Transcending the Limit of Local Window: Advanced Super-Resolution Transformer with Adaptive Token Dictionary
- Paper: https://arxiv.org/abs/2401.08209
- Code: https://github.com/LabShuHangGU/Adaptive-Token-Dictionary
Uncertainty-Aware Source-Free Adaptive Image Super-Resolution with Wavelet Augmentation Transformer
- Paper: https://arxiv.org/abs/2303.17783
- Code:
Universal Robustness via Median Randomized Smoothing for Real-World Super-Resolution
- Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Chaouai_Universal_Robustness_via_Median_Randomized_Smoothing_for_Real-World_Super-Resolution_CVPR_2024_paper.html
- Code:
Video Super-Resolution
Enhancing Video Super-Resolution via Implicit Resampling-based Alignment
- Paper: https://github.com/kai422/IART/blob/main/arxiv.pdf
- Code: https://github.com/kai422/IART
FMA-Net: Flow-Guided Dynamic Filtering and Iterative Feature Refinement with Multi-Attention for Joint Video Super-Resolution and Deblurring
- Paper: https://arxiv.org/abs/2401.03707
- Code: https://github.com/KAIST-VICLab/FMA-Net
Learning Spatial Adaptation and Temporal Coherence in Diffusion Models for Video Super-Resolution
- Paper: https://arxiv.org/abs/2403.17000
- Code:
Upscale-A-Video: Temporal-Consistent Diffusion Model for Real-World Video Super-Resolution
- Paper: https://arxiv.org/abs/2312.06640
- Code: https://github.com/sczhou/Upscale-A-Video
Video Super-Resolution Transformer with Masked Inter&Intra-Frame Attention
- Paper: https://arxiv.org/abs/2401.06312
- Code: https://github.com/LabShuHangGU/MIA-VSR
2.图像去雨(Image Deraining)
Bidirectional Multi-Scale Implicit Neural Representations for Image Deraining
- Paper: https://arxiv.org/abs/2404.01547
- Code: https://github.com/cschenxiang/NeRD-Rain
3.图像去雾(Image Dehazing)
A Semi-supervised Nighttime Dehazing Baseline with Spatial-Frequency Aware and Realistic Brightness Constraint
- Paper: https://arxiv.org/abs/2403.18548
- Code: https://github.com/Xiaofeng-life/SFSNiD
Depth Information Assisted Collaborative Mutual Promotion Network for Single Image Dehazing
- Paper: https://arxiv.org/abs/2403.01105
- Code:
ODCR: Orthogonal Decoupling Contrastive Regularization for Unpaired Image Dehazing
- Paper: https://arxiv.org/abs/2404.17825v1
- Code:
Video Dehazing
Driving-Video Dehazing with Non-Aligned Regularization for Safety Assistance
- Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Fan_Driving-Video_Dehazing_with_Non-Aligned_Regularization_for_Safety_Assistance_CVPR_2024_paper.html
- Code:
4.去模糊(Deblurring)
A Unified Framework for Microscopy Defocus Deblur with Multi-Pyramid Transformer and Contrastive Learning
- Paper: https://arxiv.org/abs/2403.02611
- Code: https://github.com/PieceZhang/MPT-CataBlur
AdaRevD: Adaptive Patch Exiting Reversible Decoder Pushes the Limit of Image Deblurring
- Paper: https://github.com/INVOKERer/AdaRevD/blob/master/AdaRevD.pdf
- Code: https://github.com/INVOKERer/AdaRevD
Blur2Blur: Blur Conversion for Unsupervised Image Deblurring on Unknown Domains
- Paper: https://arxiv.org/abs/2403.16205
- Code: https://github.com/VinAIResearch/Blur2Blur
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:
ID-Blau: Image Deblurring by Implicit Diffusion-based reBLurring AUgmentation
- Paper:https://arxiv.org/abs/2312.10998
- Code: https://github.com/plusgood-steven/ID-Blau
LDP: Language-driven Dual-Pixel Image Defocus Deblurring Network
- Paper: https://arxiv.org/abs/2307.09815
- Code: https://github.com/noxsine/LDP
Mitigating Motion Blur in Neural Radiance Fields with Events and Frames
- Paper: https://rpg.ifi.uzh.ch/docs/CVPR24_Cannici.pdf
- Code: https://github.com/uzh-rpg/EvDeblurNeRF
Motion-adaptive Separable Collaborative Filters for Blind Motion Deblurring
- Paper: https://arxiv.org/abs/2404.13153
- Code: https://github.com/ChengxuLiu/MISCFilter
Motion Blur Decomposition with Cross-shutter Guidance
- Paper: https://arxiv.org/abs/2404.01120
- Code: https://github.com/jixiang2016/dualBR
Real-World Efficient Blind Motion Deblurring via Blur Pixel Discretization
- Paper: https://arxiv.org/abs/2404.12168
- Code:
Spike-guided Motion Deblurring with Unknown Modal Spatiotemporal Alignment
- Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Zhang_Spike-guided_Motion_Deblurring_with_Unknown_Modal_Spatiotemporal_Alignment_CVPR_2024_paper.html
- Code: https://github.com/Leozhangjiyuan/UaSDN
Unsupervised Blind Image Deblurring Based on Self-Enhancement
- Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Chen_Unsupervised_Blind_Image_Deblurring_Based_on_Self-Enhancement_CVPR_2024_paper.html
- Code:
Video Deblurring
Blur-aware Spatio-temporal Sparse Transformer for Video Deblurring
- Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Zhang_Blur-aware_Spatio-temporal_Sparse_Transformer_for_Video_Deblurring_CVPR_2024_paper.html
- Code: https://github.com/huicongzhang/BSSTNet
EVS-assisted Joint Deblurring Rolling-Shutter Correction and Video Frame Interpolation through Sensor Inverse Modeling
- 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
- Code:
Frequency-aware Event-based Video Deblurring for Real-World Motion Blur
- Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Kim_Frequency-aware_Event-based_Video_Deblurring_for_Real-World_Motion_Blur_CVPR_2024_paper.html
- Code:
Latency Correction for Event-guided Deblurring and Frame Interpolation
- Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Yang_Latency_Correction_for_Event-guided_Deblurring_and_Frame_Interpolation_CVPR_2024_paper.html
- Code:
5.去噪(Denoising)
LAN: Learning to Adapt Noise for Image Denoising
- Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Kim_LAN_Learning_to_Adapt_Noise_for_Image_Denoising_CVPR_2024_paper.html
- Code:
LED: A Large-scale Real-world Paired Dataset for Event Camera Denoising
- Paper: https://arxiv.org/abs/2405.19718
- Code:
Robust Image Denoising through Adversarial Frequency Mixup
- Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Ryou_Robust_Image_Denoising_through_Adversarial_Frequency_Mixup_CVPR_2024_paper.html
- Code: https://github.com/dhryougit/AFM
Real-World Mobile Image Denoising Dataset with Efficient Baselines
- Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Flepp_Real-World_Mobile_Image_Denoising_Dataset_with_Efficient_Baselines_CVPR_2024_paper.html
- Code:
SeNM-VAE: Semi-Supervised Noise Modeling with Hierarchical Variational Autoencoder
- Paper: https://arxiv.org/abs/2403.17502
- Code: https://github.com/zhengdharia/SeNM-VAE
Transfer CLIP for Generalizable Image Denoising
- Paper: https://arxiv.org/abs/2403.15132
- Code:
Unmixing Diffusion for Self-Supervised Hyperspectral Image Denoising
- Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Zeng_Unmixing_Diffusion_for_Self-Supervised_Hyperspectral_Image_Denoising_CVPR_2024_paper.html
- Code:
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
6.图像恢复(Image Restoration)
Adapt or Perish: Adaptive Sparse Transformer with Attentive Feature Refinement for Image Restoration
- Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Zhou_Adapt_or_Perish_Adaptive_Sparse_Transformer_with_Attentive_Feature_Refinement_CVPR_2024_paper.html
- Code: https://github.com/joshyZhou/AST
Boosting Image Restoration via Priors from Pre-trained Models
- Paper: https://arxiv.org/abs/2403.06793
- Code:
CoDe: An Explicit Content Decoupling Framework for Image Restoration
- Paper: https://openaccess.thecvf.com/content/CVPR2024/html/Gu_CoDe_An_Explicit_Content_Decoupling_Framework_for_Image_Restoration_CVPR_2024_paper.html
- Code:
Deep Equilibrium Diffusion Restoration with Parallel Sampling
- Paper: https://arxiv.org/abs/2311.11600
- Code: https://github.com/caojiezhang/DeqIR
Diff-Plugin: Revitalizing Details for Diffusion-based Low-level Tasks
- Paper: https://arxiv.org/abs/2403.00644
- Code: https://github.com/yuhaoliu7456/Diff-Plugin
Distilling Semantic Priors from SAM to Efficient Image Restoration Models
- Paper: https://arxiv.org/abs/2403.16368
- Code:
DocRes: A Generalist Model Toward Unifying Document Image Restoration Tasks
- Paper: https://arxiv.org/abs/2405.04408
- Code: https://github.com/ZZZHANG-jx/DocRes
HIR-Diff: Unsupervised Hyperspectral Image Restoration Via Improved Diffusion Models
- Paper: https://arxiv.org/abs/2402.15865
- Code: https://github.com/LiPang/HIRDiff
Image Restoration by Denoising Diffusion Models With Iteratively Preconditioned Guidance
- Paper: https://arxiv.org/abs/2312.16519
- Code: https://github.com/tirer-lab/DDPG
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
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