Browse State-of-the-Art › Object State Change Classification
Object State Change Classification
6 papers with code · 0 benchmarks · 1 dataset 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
1 dataset 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.
Most implemented papers archive 2025-07-28
6 shown of 6 papers with code (9 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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19 Nov 2022 2 repositories listed Syntology ran 3 of 6 samples · 3 unverified · 6 pointer-only (licence)Masked Video Autoencoder (MVA) approaches have demonstrated their potential by significantly outperforming previous video representation learning methods.
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3 Jun 2022 2 repositories listed Syntology ran 3 of 3 samples · 0 unverified · 2 pointer-only (licence)Video-Language Pretraining (VLP), which aims to learn transferable representation to advance a wide range of video-text downstream tasks, has recently received increasing attention.
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18 Nov 2022 1 repository listedIn this report, we present our approach and empirical results of applying masked autoencoders in two egocentric video understanding tasks, namely, Object State Change Classification and PNR Temporal Localization, of…
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27 Sep 2022 1 repository listed Syntology ran 2 of 2 samples · 0 unverified · 2 pointer-only (licence)However, learning representations from videos can be challenging.
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24 Jul 2022 1 repository listedThis report describes our submission called "TarHeels" for the Ego4D: Object State Change Classification Challenge.
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4 Jul 2022 1 repository listedIn this report, we propose a video-language pretraining (VLP) based solution \cite{kevin2022egovlp} for four Ego4D challenge tasks, including Natural Language Query (NLQ), Moment Query (MQ), Object State Change…
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.
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