arXiv Computer Vision
SloMoDeblur: A Large-Scale Smartphone Image Deblurring Dataset
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arXiv AI
Jul 24
Deblurring in the Wild: A Real-World Image Deblurring Dataset from Smartphone High-Speed Videos
arXiv:2506. 19445v4 Announce Type: cross Abstract: We introduce the largest real-world image deblurring dataset constructed from smartphone slow-motion videos.
arXiv AI
Jul 24
RealVDeblur: One-Step Diffusion for Generalizable Real-World Video Deblurring
arXiv:2607. 20628v1 Announce Type: cross Abstract: Real-world video deblurring remains challenging due to diverse motion patterns, complex degradations, and the scarcity of realistic training data, yet robust restoration is critical for downstream pipelines such as mobile imaging and 3D reconstruction.
arXiv AI
Jul 1
FMA-Net++: Motion- and Exposure-Aware Joint Video Super-Resolution and Deblurring
arXiv:2512. 04390v2 Announce Type: replace-cross Abstract: Joint video super-resolution and deblurring (VSRDB) requires both efficient long-range temporal modeling and robustness to frame-wise exposure-duration variation, which changes the extent of motion blur across video frames.
arXiv Machine Learning
4d ago
AstraMoE-SR: Trajectory-Guided Diffusion for Blind Satellite Jitter Deblurring and Super-Resolution
arXiv:2609.07012v1 Announce Type: cross Abstract: Pushbroom satellite imaging couples limited spatial resolution with platform attitude instability. Platform jitter produces spatially varying motion...
arXiv Computer Vision
Aug 25
Controllable blind deblurring with diffusion models
The paper introduces SuperSharpen, a diffusion-based method for blind deblurring in professional photography that can invert unknown isotropic blur without knowing the degradation kernel. It offers explicit control over restoration strength via a blur measure and compares two conditioning strategies: a ControlNet-style adapter on a frozen backbone and full finetuning of the diffusion prior. Experiments on synthetic and real-world blur show that finetuning yields higher fidelity with fewer hallucinated details, improving perceptual quality and controllable restoration strength.
arXiv AI
Jul 24
From Attention to Frequency: Integration of Vision Transformer and FFT-ReLU for Enhanced Image Deblurring
arXiv:2511. 10806v1 Announce Type: cross Abstract: Image deblurring is vital in computer vision, aiming to recover sharp images from blurry ones caused by motion or camera shake.