Browse State-of-the-Art › Inverse-Tone-Mapping
Inverse-Tone-Mapping
21 papers with code · 1 benchmark · 1 dataset archive 2025-07-28
Benchmarks archive 2025-07-28
1 leaderboard table shown for this task, 1 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 |
|---|---|---|---|---|---|
| MSU HDR Video Reconstruction Benchmark (9 rows) | HDRTVNet | A New Journey from SDRTV to HDRTV | 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
1 dataset whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
1 subtask in the archive's task tree.
Parent tasks archive 2025-07-28
Most implemented papers archive 2025-07-28
21 shown of 21 papers with code (37 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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14 Sep 2021 2 repositories listedBased on this observation, we propose a novel normalization method called " HDR calibration " for HDR images stored in relative luminance, calibrating HDR images into a similar luminance scale according to the LDR…
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19 Apr 2021 2 repositories listedNotably, our proposed method aims to reconstruct an HDR image without knowing hardware information, including camera response function (CRF) and exposure settings.
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20 Oct 2017 2 repositories listed Syntology ran 0 of 3 samples · 3 unverifiedWe demonstrate that our approach can reconstruct high-resolution visually convincing HDR results in a wide range of situations, and that it generalizes well to reconstruction of images captured with arbitrary and…
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1 Jan 2024 1 repository listedAlthough many deep image ITM methods can generate impressive results the field of video ITM is still to be explored.
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29 Sep 2023 1 repository listedThe latter requires more efficiency, thus the pre-calculated LUT (look-up table) has become a popular solution.
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26 Aug 2023 1 repository listed Syntology ran 7 of 11 samples · 4 unverifiedExisting methods typically work well on their trained lightness conditions but perform poorly in unknown ones due to their limited generalization ability.
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8 Jul 2023 1 repository listedBut the majority of media images on the internet remain in 8-bit standard dynamic range (SDR) format.
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23 Mar 2023 1 repository listed Syntology ran 5 of 7 samples · 2 unverified · 7 pointer-only (licence)In media industry, the demand of SDR-to-HDRTV up-conversion arises when users possess HDR-WCG (high dynamic range-wide color gamut) TVs while most off-the-shelf footage is still in SDR (standard dynamic range).
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30 Sep 2022 1 repository listedMany image enhancement or editing operations, such as forward and inverse tone mapping or color grading, do not have a unique solution, but instead a range of solutions, each representing a different style.
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20 Sep 2022 1 repository listedTo achieve super-resolution inverse tone mapping, we derive a continuous representation of 360-degree imaging from the LDR panorama as a set of structured latent codes anchored to the sphere.
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23 Jul 2022 1 repository listedRecently, with the rise of high dynamic range (HDR) display devices, there is a great demand to transfer traditional low dynamic range (LDR) images into HDR versions.
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7 Jul 2022 1 repository listedJoint Super-Resolution and Inverse Tone-Mapping (joint SR-ITM) aims to increase the resolution and dynamic range of low-resolution and standard dynamic range images.
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12 Mar 2022 1 repository listedRecovering a high dynamic range (HDR) image from a single low dynamic range (LDR) image, namely inverse tone mapping (ITM), is challenging due to the lack of information in over- and under-exposed regions.
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11 Feb 2022 1 repository listedRecently, Deep Learning-based methods for inverse tone-mapping standard dynamic range (SDR) images to obtain high dynamic range (HDR) images have become very popular.
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18 Aug 2021 1 repository listedHowever, most available resources are still in standard dynamic range (SDR).
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27 May 2021 1 repository listedIn this work, we propose a novel learning-based approach using a spatially dynamic encoder-decoder network, HDRUNet, to learn an end-to-end mapping for single image HDR reconstruction with denoising and dequantization.
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2 Apr 2020 1 repository listedWe model the HDRto-LDR image formation pipeline as the (1) dynamic range clipping, (2) non-linear mapping from a camera response function, and (3) quantization.
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10 Sep 2019 1 repository listedJoint learning of super-resolution (SR) and inverse tone-mapping (ITM) has been explored recently, to convert legacy low resolution (LR) standard dynamic range (SDR) videos to high resolution (HR) high dynamic range…
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Deep SR-ITM: Joint Learning of Super-Resolution and Inverse Tone-Mapping for 4K UHD HDR Applications25 Apr 2019 1 repository listedJoint SR and ITM is an intricate task, where high frequency details must be restored for SR, jointly with the local contrast, for ITM.
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1 Sep 2018 1 repository listedBecause most images have a low dynamic range, recovering the lost dynamic range from a single low dynamic range image is still prevalent.
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6 Mar 2018 1 repository listedThis paper presents a method for generating HDR content from LDR content based on deep Convolutional Neural Networks (CNNs) termed ExpandNet.
Syntology lines on 3 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