open-mmlab/mmaction2

Health v2 · maintenance only

Adoption not part of the score

5142 stars · 1357 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

MMAction2 is OpenMMLab's PyTorch-based toolbox and benchmark for video understanding, covering action recognition, temporal action localization, and spatio-temporal action detection. It provides modular components, a large model zoo (TSN, I3D, SlowFast, TSM, X3D, NonLocal, PoseC3D, UniFormerV2), and training/evaluation pipelines.

Use cases

• classify human actions in videos
• train a SlowFast or I3D model on Kinetics
• detect when actions occur in untrimmed videos
• run spatio-temporal action detection on AVA
• benchmark video classification models
• fine-tune a pretrained video model on my own dataset
• skeleton-based action recognition with PoseC3D

When to choose

• you need state-of-the-art video action recognition or localization models in PyTorch
• you want a modular, configurable training framework with a large pretrained model zoo
• you are benchmarking video understanding approaches on standard datasets

When to avoid

• you only need simple video encoding/decoding or editing rather than ML
• you work outside PyTorch or need lightweight inference on edge devices without GPU support
• you need general image-only vision tasks better served by mmdetection or timm

Facets

library · maturity active

machine-learning deep-learning computer-vision video-processing benchmarking computer-vision deep-learning machine-learning python action-recognition video-understanding pytorch openmmlab model-zoo temporal-action-localization spatio-temporal-action-detection video linux gpu

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