Browse State-of-the-Art › HDR Reconstruction
HDR Reconstruction
23 papers with code · 0 benchmarks · 3 datasets archive 2025-07-28
Benchmarks archive 2025-07-28
No benchmark for this task in the archive.
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
1 subtask in the archive's task tree.
Most implemented papers archive 2025-07-28
23 shown of 23 papers with code (45 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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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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20 Sep 2024 1 repository listed Syntology ran 1 of 5 samples · 4 unverified · 5 pointer-only (licence)In this work, we introduce a physically-inspired remodeling of the HDR reconstruction problem in the intrinsic domain.
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7 Mar 2024 1 repository listedThis network, comprising single-frame HDR reconstruction with enhanced stop image (SHDR-ESI) and SHDR-ESI-assisted multi-exposure HDR reconstruction (SHDRA-MHDR), effectively leverages the ghost-free characteristic of…
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26 Dec 2023 1 repository listedHowever, in the case of inputting sparse Low Dynamic Range (LDR) panoramic images, NeRF often degrades with under-constrained geometry and is unable to reconstruct HDR radiance from LDR inputs.
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20 Dec 2023 1 repository listedRAW images are rarely shared mainly due to its excessive data size compared to their sRGB counterparts obtained by camera ISPs.
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3 Oct 2023 1 repository listed Syntology ran 16 of 20 samples · 4 unverified · 20 pointer-only (licence)The color component is estimated from aligned multi-exposure images, while the structure one is generated through a structure-focused network that is supervised by the color component and an input reference (\eg,…
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7 Sep 2023 1 repository listedTo address this, we propose the continuous exposure value representation (CEVR), which uses an implicit function to generate LDR images with arbitrary EVs, including those unseen during training.
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5 Sep 2023 1 repository listed Syntology ran 15 of 22 samples · 7 unverifiedUnlike existing methods, the core idea of this work is to incorporate more informative Raw sensor data to generate HDR images, aiming to recover scene information in hard regions (the darkest and brightest areas of an…
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31 Jul 2023 1 repository listedBesides, since all current datasets do not provide the corresponding relationship between the tone mapping function and the LDR image, we construct a new dataset with both synthetic and real images.
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21 Nov 2022 1 repository listedHigh dynamic range (HDR) image is widely-used in graphics and photography due to the rich information it contains.
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28 Oct 2022 1 repository listedIn this work, we propose a weakly supervised learning method that inverts the physical image formation process for HDR reconstruction via learning to generate multiple exposures from a single image.
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24 Oct 2022 1 repository listedOur experiments show that, with much fewer parameters and operations, our model can deal with the mentioned artifacts and achieve competitive performance compared with state-of-the-art methods on standard benchmarks.
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23 Oct 2022 1 repository listedWe propose a novel single-shot high dynamic range (HDR) imaging algorithm based on exposure-aware dynamic weighted learning, which reconstructs an HDR image from a spatially varying exposure (SVE) raw image.
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1 Sep 2022 1 repository listedIn this paper, we propose an algorithm unrolling approach to ghost-free HDR image synthesis algorithm that unrolls an iterative low-rank tensor completion algorithm into deep neural networks to take advantage of the…
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24 Jul 2022 1 repository listedAs the problem of reconstructing high dynamic range (HDR) images from a single exposure has attracted much research effort, it is essential to provide a robust protocol and clear guidelines on how to evaluate and…
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19 Aug 2021 1 repository listedHere, we reproduce a typical evaluation using existing as well as simulated SI-HDR methods to demonstrate how different aspects of the problem affect objective quality metrics.
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2 Jun 2021 1 repository listedThis paper reviews the first challenge on high-dynamic range (HDR) imaging that was part of the New Trends in Image Restoration and Enhancement (NTIRE) workshop, held in conjunction with CVPR 2021.
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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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27 Mar 2021 1 repository listedSecondly, we conduct more sophisticated alignment and temporal fusion in the feature space of the coarse HDR video to produce better reconstruction.
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3 Jul 2020 1 repository listed Syntology ran 0 of 11 samples · 11 unverifiedTo address these two problems, we propose in this paper a novel GAN-based model, HDR-GAN, for synthesizing HDR images from multi-exposed LDR images.
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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 Feb 2020 1 repository listedIn NHDRRnet, we first adopt an Unet architecture to fuse all inputs and map the fusion results into a low-dimensional deep feature space.
Syntology lines on 5 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.
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