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Found 7 papers, 4 papers with code
Real-World Blur Dataset for Learning and Benchmarking Deblurring Algorithms
To collect our dataset, we build an image acquisition system to simultaneously capture geometrically aligned pairs of blurred and sharp images, and develop a postprocessing method to produce high-quality ground truth images.
Gyro-based Neural Single Image Deblurring
To handle gyro error, GyroDeblurNet is equipped with two novel neural network blocks: a gyro refinement block and a gyro deblurring block.
Deep Hybrid Camera Deblurring
We simultaneously capture a long exposure wide-angle image and ultra-wide burst images from a smartphone, and use the sharp burst to estimate blur kernels for deblurring the wide-angle image.
ExBluRF: Efficient Radiance Fields for Extreme Motion Blurred Images
We minimize the photo-consistency loss on blurred image space and obtain the sharp radiance fields with camera trajectories that explain the blur of all images.
Human Pose Estimation in Extremely Low-Light Conditions
We study human pose estimation in extremely low-light images.
Realistic Blur Synthesis for Learning Image Deblurring
To this end, we present RSBlur, a novel dataset with real blurred images and the corresponding sharp image sequences to enable a detailed analysis of the difference between real and synthetic blur.
Ranked #1 on
Deblurring
on RSBlur (trained on synthetic)
Iterative Filter Adaptive Network for Single Image Defocus Deblurring
We propose a novel end-to-end learning-based approach for single image defocus deblurring.
Ranked #3 on
Image Defocus Deblurring
on RealDOF
