Image Deblurring
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Benchmarks
GoPro
HIDE
CelebA
HIDE (trained on GOPRO)
ImageNet
Real-world Dataset
RealBlur-J
RealBlur-R
Most implemented
Simple Baselines for Image Restoration
Restormer: Efficient Transformer for High-Resolution Image Restoration
Multi-Stage Progressive Image Restoration
DeblurGAN-v2: Deblurring (Orders-of-Magnitude) Faster and Better
Intriguing Findings of Frequency Selection for Image Deblurring
Papers
GS-RealBlur: A Flexible Data Acquisition Framework for Real-World Image Deblurring
High-quality, large-scale paired data is essential for training learning-based image deblurring models. However, synthetic blurry images generally lack realism, while real-world captured images require complex and inflex…
Image DeblurringDICT: Data Injection and Contrastive Trajectory Refinement for Conditional Image Generation with Diffusion Models
Diffusion models have become a dominant paradigm for conditional image generation, yet existing approaches generally follow two directions: task-specific designs that can improve performance but limit generalization, and…
Conditional Image GenerationImage Super-ResolutionImage DeblurringStyle TransferLeveraging Phase Information to Boost Unrolled Network Learning for Image Deblurring
While most image deblurring techniques directly restore the spatial image variable, we propose an amplitude and phase decomposition recognizing the importance of accurate phase estimation in recovering sharp image detail…
Image DeblurringCogSENet: Blind Image Deblurring with Blur-Conditioned Semantic Routing and Explicit Frequency Fusion
Blind image deblurring demands the recovery of high-fidelity details and coherent structures from complex, unknown degradations. Current blind image deblurring methods struggle with real-world, spatially varying degradat…
Image DeblurringFSM-Net: An Efficient Frequency-Spatial Network for Real-World Deblurring
Real-world image deblurring demands both high-fidelity restoration and computational efficiency, a balance existing methods often struggle to achieve. In this paper, we propose FSM-Net (Frequency-Spatial Multi-branch Net…
Computational EfficiencyImage RestorationImage DeblurringStop Denoising Your Blurs
In recent times, diffusion models have achieved remarkable performance in image restoration tasks. Their core mechanism relies on the restricted presumption of degradation prior to the additive noise operation. However, …
Image RestorationImage Deblurring