https://github.com/Talented-Q/Restorer
공식 코드Restorer: Removing Multi-Degradation with All-Axis Attention and Prompt Guidance
Papers with Code 아카이브
Deblurring
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 보존된 평가 기록
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Deblurring is a computer vision task that involves removing the blurring artifacts from images or videos to restore the original, sharp content. Blurring can be caused by various factors such as camera shake, fast motion, and out-of-focus objects, and can result in a loss of detail and quality in the captured images. The goal of deblurring is to produce a clear, high-quality image that accurately represents the original scene.
<span style="color:grey; opacity: 0.6">( Image credit: Deblurring Face Images using Uncertainty Guided Multi-Stream Semantic Networks )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/TimRoith/BregmanLearning
공식 코드https://github.com/Tombs98/ALGNet
공식 코드Learning Enriched Features via Selective State Spaces Model for Efficient Image Deblurring
https://github.com/Tombs98/CAPTNet
공식 코드Prompt-based Ingredient-Oriented All-in-One Image Restoration
https://github.com/Tombs98/M3SNet
공식 코드A Mountain-Shaped Single-Stage Network for Accurate Image Restoration
https://github.com/Vibhu04/Deblurring-Variational-Autoencoders-with-STFT
공식 코드Short-Time Fourier Transform for deblurring Variational Autoencoders
https://github.com/VinAIResearch/blur-kernel-space-exploring
공식 코드https://github.com/Vinayak-VG/GAURA
공식 코드GAURA: Generalizable Approach for Unified Restoration and Rendering of Arbitrary Views
https://github.com/WU-CVGL/BAD-Gaussians
공식 코드https://github.com/WU-CVGL/BAD-NeRF
공식 코드https://github.com/WeishengDong/DPDNN_PyTorch
공식 코드Denoising Prior Driven Deep Neural Network for Image Restoration
https://github.com/XLearning-SCU/2025-CVPR-MaIR
공식 코드MaIR: A Locality- and Continuity-Preserving Mamba for Image Restoration
https://github.com/York-SDCNLab/Ghost-DeblurGAN
공식 코드https://github.com/ZhendongWang6/Uformer
공식 코드Uformer: A General U-Shaped Transformer for Image Restoration
https://github.com/ahupujr/ntire2025_eventdeblur_challenge
공식 코드NTIRE 2025 Challenge on Event-Based Image Deblurring: Methods and Results
https://github.com/ahupujr/refid
공식 코드A Unified Framework for Event-based Frame Interpolation with Ad-hoc Deblurring in the Wild
https://github.com/aimerykong/predictive-filter-flow
공식 코드https://github.com/algolzw/image-restoration-sde
공식 코드Image Restoration with Mean-Reverting Stochastic Differential Equations
https://github.com/alikaraali/svbr_net_icip
공식 코드SVBR-NET: A Non-Blind Spatially Varying Defocus Blur Removal Network
https://github.com/anastasiia-kornilova/MMDF
공식 코드https://github.com/annegnx/PnP-Flow
공식 코드PnP-Flow: Plug-and-Play Image Restoration with Flow Matching
https://github.com/anshulbshah/Blurred-Image-to-Video
공식 코드https://github.com/arghyasinha/tsp-kernel-denoiser
공식 코드Linear Convergence of Plug-and-Play Algorithms with Kernel Denoisers
https://github.com/aurangau/ICIP2024
공식 코드https://github.com/auto-dog/moac_deep
공식 코드Misaligned Over-The-Air Computation of Multi-Sensor Data with Wiener-Denoiser Network
https://github.com/axium/Blind-Image-Deconvolution-using-Deep-Generative-Priors
공식 코드Blind Image Deconvolution using Pretrained Generative Priors
https://github.com/bahjat-kawar/ddrm
공식 코드https://github.com/bahjat-kawar/snips_torch
공식 코드https://github.com/benhenryl/sharpnerf
공식 코드Sharp-NeRF: Grid-based Fast Deblurring Neural Radiance Fields Using Sharpness Prior
https://github.com/bestrivenzc/CZ-Net
공식 코드CrossZoom: Simultaneously Motion Deblurring and Event Super-Resolving
https://github.com/bilocq/trust-the-critics-2
공식 코드https://github.com/bilocq/wgan-gp-benchmark
공식 코드https://github.com/bnm6900030/swintormer
공식 코드Efficient Image Deblurring Networks based on Diffusion Models
https://github.com/bob831009/raw_image_deblurring
공식 코드https://github.com/c-yn/adair
공식 코드AdaIR: Adaptive All-in-One Image Restoration via Frequency Mining and Modulation
https://github.com/caiziruo/nf-ula
공식 코드NF-ULA: Langevin Monte Carlo with Normalizing Flow Prior for Imaging Inverse Problems
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.