Browse State-of-the-Art › Multi-Frame Super-Resolution
Multi-Frame Super-Resolution
16 papers with code · 1 benchmark · 3 datasets archive 2025-07-28
When multiple images of the same view are taken from slightly different positions, perhaps also at different times, then they collectively contain more information than any single image on its own. Multi-Frame Super-Resolution fuses these low-res inputs into a composite high-res image that can reveal some of the original detail that cannot be recovered from any low-res image alone.
( Credit: HighRes-net )
Description from the archive 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 |
|---|---|---|---|---|---|
| PROBA-V (8 rows) | TR-MISR | TR-MISR: Multiimage Super-Resolution Based on Feature Fusion With... | 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
16 shown of 16 papers with code (34 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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27 Aug 2018 12 repositories listed Syntology ran 0 of 17 samples · 17 unverified · 2 pointer-only (licence)Keras-based implementation of WDSR, EDSR and SRGAN for single image super-resolution
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26 Jan 2021 3 repositories listed Syntology ran 6 of 7 samples · 1 unverified · 7 pointer-only (licence)We propose a novel architecture for the burst super-resolution task.
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8 May 2019 3 repositories listedIn this paper, we supplant the use of traditional demosaicing in single-frame and burst photography pipelines with a multiframe super-resolution algorithm that creates a complete RGB image directly from a burst of CFA…
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18 Aug 2021 2 repositories listedThe deep reparametrization allows us to directly model the image formation process in the latent space, and to integrate learned image priors into the prediction.
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15 Jun 2021 2 repositories listedWe propose a novel architecture to handle the problem of multi-frame super-resolution (MFSR).
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6 Jul 2020 2 repositories listedConvolutional Neural Networks (CNNs) have been consistently proved state-of-the-art results in image Super-Resolution (SR), representing an exceptional opportunity for the remote sensing field to extract further…
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15 Feb 2020 2 repositories listedMulti-frame Super-Resolution (MFSR) offers a more grounded approach to the ill-posed problem, by conditioning on multiple low-resolution views.
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21 Sep 2024 1 repository listedHowever, the existing MFSR suffers from misalignments between the reference and source frames due to the limitations of DCN, such as small receptive fields and the predefined number of kernels.
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27 Feb 2024 1 repository listedBurst super-resolution or multi-frame super-resolution (MFSR) has gained significant attention in recent years, particularly in the context of mobile photography.
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6 Mar 2023 1 repository listedSuper-resolution is the process of obtaining a high-resolution image from one or more low-resolution images.
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13 Jul 2022 1 repository listed Syntology ran 0 of 9 samples · 9 unverifiedWe hereby hope to foster broad-spectrum applications of ML to satellite imagery, and possibly develop from free public low-resolution Sentinel2 imagery the same power of analysis allowed by costly private…
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18 Apr 2022 1 repository listed Syntology ran 5 of 13 samples · 8 unverifiedTo overcome the challenges in BurstSR, we propose a Burst Super-Resolution Transformer (BSRT), which can significantly improve the capability of extracting inter-frame information and reconstruction.
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5 Feb 2022 1 repository listedIn addition, TR-MISR adopts an additional learnable embedding vector that fuses these vectors to restore the details to the greatest extent.
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26 May 2021 1 repository listed Syntology ran 0 of 8 samples · 8 unverifiedHowever, existing models have neglected the issue of temporal permutation, whereby the temporal ordering of the input images does not carry any relevant information for the super-resolution task and causes such models…
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1 Jan 2020 1 repository listedMulti-frame Super-Resolution (MFSR) offers a more grounded approach to the ill-posed problem, by conditioning on multiple low-resolution views.
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15 Jul 2019 1 repository listedThis novel framework integrates the spatial registration task directly inside the CNN, and allows to exploit the representation learning capabilities of the network to enhance registration accuracy.
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.
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