Methods › Computer Vision › Action Recognition Models › TDN

Temporaral Difference Network

TDN

8 papers tagged archive 2025-07-28

Introduced by LiMin Wang et al. in TDN: Temporal Difference Networks for Efficient Action Recognition

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

TDN, or Temporaral Difference Network, is an action recognition model that aims to capture multi-scale temporal information. To fully capture temporal information over the entire video, the TDN is established with a two-level difference modeling paradigm. Specifically, for local motion modeling, temporal difference over consecutive frames is used to supply 2D CNNs with finer motion pattern, while for global motion modeling, temporal difference across segments is incorporated to capture long-range structure for motion feature excitation.

PaperSource

Papers archive 2025-07-28

8 shown of 8, 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.

Tasks archive 2025-07-28

20 shown of 21 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Action Recognition2
Action Recognition In Videos2
Denoising2
Transfer Learning2
Action Classification1
Action Localization1
Chemical Process1
Diagnostic1
Fault Detection1
Fault Diagnosis1
Fault localization1
Human Detection1
Person Re-Identification1
Person Search1
Representation Learning1
Retrieval1
Temporal Action Localization1
Topological Data Analysis1
Weakly-supervised Learning1
Weakly-supervised Temporal Action Localization1

Usage over time archive 2025-07-28

Papers per year tagged with TDN: 2020 to 2024, peak 3 3 0 2020: 1 paper 2020 2021: 3 papers 2021 2022: 1 paper 2022 2023: 1 paper 2023 2024: 2 papers 2024
Papers per year the archive tags with this method, by the paper's archive date (8 dated). Bars are counts, not a trend claim.

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

Action Recognition Models

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