Reflection Removal
29 papers with code • 5 benchmarks • 3 datasets
Benchmarks
These leaderboards are used to track progress in Reflection Removal
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CDR
SlowFlow
PolarRR
Latest papers with no code
Learning to Deblur Polarized Images
However, since the on-chip micro-polarizers block part of the light so that the sensor often requires a longer exposure time, the captured polarized images are prone to motion blur caused by camera shakes, leading to noticeable degradation in the computed DoP and AoP.
Single Image Reflection Removal with Reflection Intensity Prior Knowledge
In this paper, we propose a general reflection intensity prior that captures the intensity of the reflection phenomenon and demonstrate its effectiveness.
Fooling Polarization-based Vision using Locally Controllable Polarizing Projection
If so, is that possible to realize these adversarial attacks in the physical world, without being perceived by human eyes?
Variational Degeneration to Structural Refinement: A Unified Framework for Superimposed Image Decomposition
Several unified frameworks have been proposed that can handle different types of degradation in superimposed image decomposition.
Improved Multiple-Image-Based Reflection Removal Algorithm Using Deep Neural Networks
In this paper, a novel deep neural network approach for solving the reflection problem in imaging is presented.
Highlight Specular Reflection Separation based on Tensor Low-rank and Sparse Decomposition Using Polarimetric Cues
This regularization boosts the performance of the method to recover an accurate diffuse image by handling the color distortion, a common problem of chromaticity-based methods, especially in case of strong specular reflection.
DURRNet: Deep Unfolded Single Image Reflection Removal Network
With the deep unrolling technique, we build the DURRNet with ProxNets to model natural image priors and ProxInvNets which are constructed with invertible networks to impose the exclusion prior.
U2-Former: A Nested U-shaped Transformer for Image Restoration
While Transformer has achieved remarkable performance in various high-level vision tasks, it is still challenging to exploit the full potential of Transformer in image restoration.
A Categorized Reflection Removal Dataset with Diverse Real-world Scenes
Due to the lack of a large-scale reflection removal dataset with diverse real-world scenes, many existing reflection removal methods are trained on synthetic data plus a small amount of real-world data, which makes it difficult to evaluate the strengths or weaknesses of different reflection removal methods thoroughly.
Panoramic Image Reflection Removal
This paper studies the problem of panoramic image reflection removal, aiming at reliving the content ambiguity between reflection and transmission scenes.
