Browse State-of-the-Art › Supervised Video Summarization
Supervised Video Summarization
12 papers with code · 2 benchmarks · 4 datasets archive 2025-07-28
Supervised video summarization rely on datasets with human-labeled ground-truth annotations (either in the form of video summaries, as in the case of the SumMe dataset, or in the form of frame-level importance scores, as in the case of the TVSum dataset), based on which they try to discover the underlying criterion for video frame/fragment selection and video summarization.
Source: Video Summarization Using Deep Neural Networks: A Survey
Description from the archive archive 2025-07-28; Papers-with-Code links inside it are rewritten to this site.
Benchmarks archive 2025-07-28
2 leaderboard tables shown for this task, 2 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 |
|---|---|---|---|---|---|
| SumMe (21 rows) | PGL-SUM (maximum learning capacity) | Combining Global and Local Attention with Positional Encoding for... | code | — | Compare |
| TvSum (21 rows) | MAVS [DBLP:conf/mm/FengLKZ18] | Supervised Video Summarization via Multiple Feature Sets 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
4 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
12 shown of 12 papers with code (28 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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29 Dec 2017 6 repositories listed Syntology ran 1 of 1 samples · 0 unverifiedVideo summarization aims to facilitate large-scale video browsing by producing short, concise summaries that are diverse and representative of original videos.
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23 Apr 2021 3 repositories listedThe proposed architecture utilizes an attention mechanism before fusing motion features and features representing the (static) visual content, i.
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29 Sep 2019 3 repositories listedIn this paper, we propose Test-Time Training, a general approach for improving the performance of predictive models when training and test data come from different distributions.
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13 Mar 2023 2 repositories listedThe goal of multimodal summarization is to extract the most important information from different modalities to form output summaries.
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7 Jan 2022 2 repositories listedConsidering that the annotation of large-scale datasets is time-consuming, we propose a multimodal self-supervised learning framework to obtain semantic representations of videos, which benefits the video summarization…
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27 Dec 2021 2 repositories listedVideo summarization aims to automatically generate a summary (storyboard or video skim) of a video, which can facilitate large-scale video retrieval and browsing.
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20 May 2024 1 repository listed Syntology ran 7 of 8 samples · 1 unverifiedVideo summarization aims to generate a concise representation of a video, capturing its essential content and key moments while reducing its overall length.
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1 Dec 2021 1 repository listedThis paper presents a new method for supervised video summarization.
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1 Jul 2021 1 repository listedA generic video summary is an abridged version of a video that conveys the whole story and features the most important scenes.
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9 Jun 2021 1 repository listedWith the exponential growth of video data, video summarization techniques are urgently needed for reducing people’s efforts in the videos' content exploration by generating succinct but informative summaries from…
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1 Dec 2020 1 repository listedIn this paper, we propose a Detect-to-Summarize network (DSNet) framework for supervised video summarization.
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24 Nov 2018 1 repository listedThe proposed variance loss allows a network to predict output scores for each frame with high discrepancy which enables effective feature learning and significantly improves model performance.
Syntology lines on 2 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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