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Found 6 papers, 4 papers with code
PANet: A Physics-guided Parametric Augmentation Net for Image Dehazing by Hazing
Image dehazing faces challenges when dealing with hazy images in real-world scenarios.
ViStripformer: A Token-Efficient Transformer for Versatile Video Restoration
Besides, ViStripformer is an effective and efficient transformer architecture with much lower memory usage than the vanilla transformer.
ID-Blau: Image Deblurring by Implicit Diffusion-based reBLurring AUgmentation
We parameterize the blur patterns of a blurred image with their orientations and magnitudes as a pixel-wise blur condition map to simulate motion trajectories and implicitly represent them in a continuous space.
Meta Transferring for Deblurring
Most previous deblurring methods were built with a generic model trained on blurred images and their sharp counterparts.
Stripformer: Strip Transformer for Fast Image Deblurring
Images taken in dynamic scenes may contain unwanted motion blur, which significantly degrades visual quality.
Ranked #2 on
Deblurring
on RealBlur-R
BANet: Blur-aware Attention Networks for Dynamic Scene Deblurring
Image motion blur results from a combination of object motions and camera shakes, and such blurring effect is generally directional and non-uniform.
Ranked #5 on
Deblurring
on RealBlur-R
