Temporal Segment Networks (TSN)

Health v2 · maintenance only

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1577 stars · 464 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Official code and pretrained models for Temporal Segment Networks (TSN), a deep learning framework for video action recognition published at ECCV 2016/TPAMI 2018. It provides Caffe-based training/testing pipelines plus an experimental PyTorch implementation, with the authors recommending MMAction for new work.

Use cases

• reproduce TSN action recognition results from the ECCV 2016 paper
• classify human actions in videos with pretrained Kinetics models
• train a video action recognition model on a custom dataset
• extract frames and optical flow from videos for training
• fine-tune TSN models for transfer learning on new video datasets
• compare video action recognition baselines for research

When to choose

• you need the original TSN implementation to reproduce paper results
• you are a Caffe user needing maintained TSN support
• you want pretrained Kinetics action recognition weights from the authors
• you are studying or extending classic video understanding methods

When to avoid

• you are starting a new action recognition project - use MMAction2 instead
• you need a maintained, modern PyTorch video toolbox
• you require Windows or non-Linux platform support
• you want production-ready video classification without research setup effort

Facets

library · maturity maintenance

machine-learning deep-learning video-processing computer-vision machine-learning computer-vision deep-learning python action-recognition video-understanding temporal-segment-networks caffe pytorch research-code optical-flow eccv-2016 video linux docker gpu

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For agents

markdown · JSON · MCP: product_card(name="yjxiong/temporal-segment-networks")