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
Improving Single-Image Defocus Deblurring: How Dual-Pixel Images Help Through Multi-Task Learning
Abdullah-Abuolaim/multi-task-defocus-deblurring-dual-pixel-nimat
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Specifically, we show that jointly learning to predict the two DP views from a single blurry input image improves the network's ability to learn to deblur the image.
Single Image Reflection Removal With Absorption Effect
In this paper, we consider the absorption effect for the problem of single image reflection removal.
Robust Reflection Removal with Reflection-free Flash-only Cues
ChenyangLEI/flash-reflection-removal
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CVPR 2021
The flash-only image is equivalent to an image taken in a dark environment with only a flash on.
V-DESIRR: Very Fast Deep Embedded Single Image Reflection Removal
Our method processes the corrupted image in two stages, a Low Scale Sub-network (LSSNet) to process the lowest scale and a Progressive Inference (PI) stage to process all the higher scales.
Location-aware Single Image Reflection Removal
zdlarr/Location-aware-SIRR
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ICCV 2021
It is beneficial to strong reflection detection and substantially improves the quality of reflection removal results.
Two-Stage Single Image Reflection Removal with Reflection-Aware Guidance
liyucs/RAGNet
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To be specific, the reflection layer is firstly estimated due to that it generally is much simpler and is relatively easier to estimate.
Deep-Masking Generative Network: A Unified Framework for Background Restoration from Superimposed Images
funkdub/DMGN
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In this work we present the Deep-Masking Generative Network (DMGN), which is a unified framework for background restoration from the superimposed images and is able to cope with different types of noise.
Learning to See Through Obstructions
alex04072000/ObstructionRemoval
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CVPR 2020
We present a learning-based approach for removing unwanted obstructions, such as window reflections, fence occlusions or raindrops, from a short sequence of images captured by a moving camera.
Polarized Reflection Removal with Perfect Alignment in the Wild
ChenyangLEI/CVPR2020-Polarized-Reflection-Removal-with-Perfect-Alignment
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CVPR 2020
We present a novel formulation to removing reflection from polarized images in the wild.
Single Image Reflection Removal through Cascaded Refinement
IBCLN is a cascaded network that iteratively refines the estimates of transmission and reflection layers in a manner that they can boost the prediction quality to each other, and information across steps of the cascade is transferred using an LSTM.
