Methods › Computer Vision › Video Sampling › Temporal Jittering
Temporal Jittering
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
Temporal Jittering is a method used in deep learning for video, where we sample multiple training clips from each video with random start times during at every epoch.
Papers archive 2025-07-28
5 shown of 5, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
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Adaptive and Temporally Consistent Gaussian Surfels for Multi-view Dynamic Reconstruction 10 Nov 2024 · 0 repositories · arXiv:2411.06602
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LEO: Generative Latent Image Animator for Human Video Synthesis 6 May 2023 · 5 repositories · arXiv:2305.03989
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Learning Variational Motion Prior for Video-based Motion Capture 27 Oct 2022 · 0 repositories · arXiv:2210.15134
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A Proposal-Based Solution to Spatio-Temporal Action Detection in Untrimmed Videos 20 Nov 2018 · 0 repositories · arXiv:1811.08496
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A Closer Look at Spatiotemporal Convolutions for Action Recognition 30 Nov 2017 · 24 repositories · arXiv:1711.11248Syntology ran 1 of 4 samples · 3 unverified · 4 pointer-only (licence)
Tasks archive 2025-07-28
13 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
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