Browse State-of-the-Art › Reflection Removal
Reflection Removal
38 papers with code · 5 benchmarks · 3 datasets archive 2025-07-28
Remove the spots from mirror and clear the picture
Description from the archive archive 2025-07-28.
Benchmarks archive 2025-07-28
5 leaderboard tables shown for this task, 5 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.
| Dataset | Best model (first row in archive order) | Paper | Code | Syntology | Compare |
|---|---|---|---|---|---|
| Real20 (8 rows) | RDNet | Reversible Decoupling Network for Single Image Reflection Removal | code | — | Compare |
| SIR^2(Objects) (7 rows) | RDNet | Reversible Decoupling Network for Single Image Reflection Removal | code | — | Compare |
| SIR^2(Postcard) (6 rows) | RDNet | Reversible Decoupling Network for Single Image Reflection Removal | code | — | Compare |
| SIR^2(Wild) (6 rows) | RDNet | Reversible Decoupling Network for Single Image Reflection Removal | code | — | Compare |
| Nature (5 rows) | DAI | Dereflection Any Image with Diffusion Priors and Diversified Data | code | — | Compare |
Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
3 datasets whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
No subtask under this task in the archive's task tree.
Parent tasks archive 2025-07-28
Most implemented papers archive 2025-07-28
30 shown of 38 papers with code (81 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
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15 Nov 2019 3 repositories listedIBCLN 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…
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14 Jun 2018 3 repositories listed Syntology ran 0 of 3 samples · 3 unverifiedOur loss function includes two perceptual losses: a feature loss from a visual perception network, and an adversarial loss that encodes characteristics of images in the transmission layers.
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31 Jan 2018 3 repositories listedImage of a scene captured through a piece of transparent and reflective material, such as glass, is often spoiled by a superimposed layer of reflection image.
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10 Jun 2025 1 repository listedFollowing this paradigm, we collect a Real-world, Diverse, and Pixel-aligned dataset (named OpenRR-1k dataset), which contains 1, 000 high-quality transmission-reflection image pairs collected in the wild.
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23 Mar 2025 1 repository listedTo this end, we construct a large-scale dataset, PolaRGB, for Polarization-based reflection removal of RGB images, which enables us to train models that generalize effectively across a wide range of real-world scenarios.
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21 Mar 2025 1 repository listedReflection removal of a single image remains a highly challenging task due to the complex entanglement between target scenes and unwanted reflections.
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3 Mar 2025 1 repository listedSingle Image Reflection Removal (SIRR) is a canonical blind source separation problem and refers to the issue of separating a reflection-contaminated image into a transmission and a reflection image.
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12 Feb 2025 1 repository listedThe phenomenon of reflection is quite common in digital images, posing significant challenges for various applications such as computer vision, photography, and image processing.
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11 Dec 2024 1 repository listedIn this paper, we present a novel approach for image reflection removal using a single image.
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10 Oct 2024 1 repository listedRecent deep-learning-based approaches to single-image reflection removal have shown promising advances, primarily for two reasons: 1) the utilization of recognition-pretrained features as inputs, and 2) the design of…
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3 Jun 2024 1 repository listedSecondly, we devise a contrastive mask-guided reflection removal network that comprises a newly proposed contrastive guidance interaction block (CGIB).
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28 Feb 2024 1 repository listedThis paper addresses reflection removal, which is the task of separating reflection components from a captured image and deriving the image with only transmission components.
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4 Feb 2024 1 repository listedFor 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.
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29 Nov 2023 1 repository listedThis 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…
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19 Aug 2023 1 repository listed Syntology ran 15 of 19 samples · 4 unverifiedThe reflection superposition phenomenon is complex and widely distributed in the real world, which derives various simplified linear and nonlinear formulations of the problem.
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1 Aug 2023 1 repository listedTo the best of our knowledge, these two datasets are the first largest-scale UHD datasets for SIRR.
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1 Jan 2023 1 repository listedThis paper addresses the problem of robust deep single-image reflection removal (SIRR) against adversarial attacks.
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5 Nov 2022 1 repository listed Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)We propose a simple yet effective reflection-free cue for robust reflection removal from a pair of flash and ambient (no-flash) images.
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16 Jul 2022 1 repository listedWhile the research on image background restoration from regular size of degraded images has achieved remarkable progress, restoring ultra high-resolution (e.
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4 Apr 2022 1 repository listedMeanwhile, diverse testing sets are also provided with different types of reflection and scenes.
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12 Mar 2022 1 repository listedWith 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.
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20 Oct 2021 1 repository listed Syntology ran 4 of 8 samples · 4 unverifiedSingle image reflection separation (SIRS), as a representative blind source separation task, aims to recover two layers, i.
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11 Aug 2021 1 repository listedSpecifically, 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.
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19 Jun 2021 1 repository listedIn this paper, we consider the absorption effect for the problem of single image reflection removal.
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7 Mar 2021 1 repository listedThe flash-only image is equivalent to an image taken in a dark environment with only a flash on.
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1 Jan 2021 1 repository listedOur 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.
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13 Dec 2020 1 repository listedIt is beneficial to strong reflection detection and substantially improves the quality of reflection removal results.
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2 Dec 2020 1 repository listedTo be specific, the reflection layer is firstly estimated due to that it generally is much simpler and is relatively easier to estimate.
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9 Oct 2020 1 repository listedIn 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.
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2 Apr 2020 1 repository listedWe 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.
Syntology lines on 4 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections