Browse State-of-the-Art › Long Term Action Anticipation
Long Term Action Anticipation
13 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
13 shown of 13 papers with code (22 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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1 Jan 2025 1 repository listedExtensive experiments on benchmark datasets demonstrate the superiority of the proposed ActionLLM framework, encouraging a promising direction to explore LLMs in the context of action anticipation.
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16 Jul 2024 1 repository listedAs generator, we introduce a Gated Anticipation Network (GTAN) to model both observed and unobserved frames of a video in a mutual representation.
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26 Jun 2024 1 repository listed Syntology ran 11 of 15 samples · 4 unverified · 15 pointer-only (licence)In this report, we present our solutions to the EgoVis Challenges in CVPR 2024, including five tracks in the Ego4D challenge and three tracks in the EPIC-Kitchens challenge.
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31 Oct 2023 1 repository listed Syntology ran 1 of 5 samples · 4 unverifiedTo recognize and predict human-object interactions, we use a Transformer-based neural architecture which allows the "retrieval" of relevant objects for action anticipation at various time scales.
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31 Jul 2023 1 repository listed Syntology ran 2 of 2 samples · 0 unverifiedWe propose to formulate the LTA task from two perspectives: a bottom-up approach that predicts the next actions autoregressively by modeling temporal dynamics; and a top-down approach that infers the goal of the actor…
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4 Jul 2023 1 repository listed Syntology ran 1 of 2 samples · 1 unverifiedIn this report, we describe the technical details of our approach for the Ego4D Long-Term Action Anticipation Challenge 2023.
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28 Jun 2023 1 repository listed Syntology ran 1 of 6 samples · 5 unverifiedWe present Palm, a solution to the Long-Term Action Anticipation (LTA) task utilizing vision-language and large language models.
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5 Jan 2023 1 repository listed Syntology ran 4 of 5 samples · 1 unverified · 5 pointer-only (licence)Video-language embeddings are a promising avenue for injecting semantics into visual representations, but existing methods capture only short-term associations between seconds-long video clips and their accompanying…
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20 Oct 2022 1 repository listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)Action anticipation involves predicting future actions having observed the initial portion of a video.
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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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25 Jul 2022 1 repository listed Syntology ran 0 of 3 samples · 3 unverifiedOur framework first extracts two level of human information over the N observed videos human actions through a Hierarchical Multi-task MLP Mixer (H3M).
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1 Jul 2022 1 repository listed Syntology ran 1 of 9 samples · 8 unverifiedThe CLIP embedding provides fine-grained understanding of objects relevant for an action whereas the slowfast network is responsible for modeling temporal information within a video clip of few frames.
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27 May 2022 1 repository listed Syntology ran 5 of 8 samples · 3 unverified · 8 pointer-only (licence)The task of predicting future actions from a video is crucial for a real-world agent interacting with others.
Syntology lines on 11 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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