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
Most implemented papers
Adaptive Network Combination for Single-Image Reflection Removal: A Domain Generalization Perspective
csmliu/adanec
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Meanwhile, diverse testing sets are also provided with different types of reflection and scenes.
Global-Local Stepwise Generative Network for Ultra High-Resolution Image Restoration
f-frida/glsgn
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While the research on image background restoration from regular size of degraded images has achieved remarkable progress, restoring ultra high-resolution (e. g., 4K) images remains an extremely challenging task due to the explosion of computational complexity and memory usage, as well as the deficiency of annotated data.
Robust Reflection Removal with Flash-only Cues in the Wild
ChenyangLEI/flash-reflection-removal
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We propose a simple yet effective reflection-free cue for robust reflection removal from a pair of flash and ambient (no-flash) images.
Robust Single Image Reflection Removal Against Adversarial Attacks
ZhenboSong/RobustSIRR
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CVPR 2023
This paper addresses the problem of robust deep single-image reflection removal (SIRR) against adversarial attacks.
Benchmarking Ultra-High-Definition Image Reflection Removal
liar-zzy/benchmarking-ultra-high-definition-single-image-reflection-removal
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To the best of our knowledge, these two datasets are the first largest-scale UHD datasets for SIRR.
Single Image Reflection Separation via Component Synergy
The reflection superposition phenomenon is complex and widely distributed in the real world, which derives various simplified linear and nonlinear formulations of the problem.
Revisiting Single Image Reflection Removal In the Wild
zhuyr97/Reflection_RemoVal_CVPR2024
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This research focuses on the issue of single-image reflection removal (SIRR) in real-world conditions, examining it from two angles: the collection pipeline of real reflection pairs and the perception of real reflection locations.
PromptRR: Diffusion Models as Prompt Generators for Single Image Reflection Removal
For the prompt generation, we first propose a prompt pre-training strategy to train a frequency prompt encoder that encodes the ground-truth image into LF and HF prompts.
Reflection Removal Using Recurrent Polarization-to-Polarization Network
This paper addresses reflection removal, which is the task of separating reflection components from a captured image and deriving the image with only transmission components.
