MMACTION2: An Introduction to OpenMMLab's Video Understanding Toolbox
Introduction
MMAction2 is an open-source toolbox designed for video understanding tasks, built on the powerful PyTorch deep learning framework. It is a component of the OpenMMLab project, which focuses on creating advanced tools for computer vision research and applications.
What's New
As of the latest release on October 12, 2023, MMACTION2 has introduced several noteworthy features:
- Integration of VindLU multi-modality algorithms and ActionClip training support.
- Introduction of lightweight models MobileOne TSN/TSM.
- Support for video retrieval dataset MSVD.
- Features for SlowOnly K700 to aid in training localization models.
- Video and audio demo capabilities have been incorporated.
The project has also switched its default branch to main, encouraging users to migrate for better model support and simpler coding practices.
Major Features
Here are some of the key features that make MMACTION2 stand out:
- Modular Design: The toolbox decomposes video understanding frameworks into identifiable components, allowing users to mix and match modules to create custom frameworks.
- Support for Major Video Understanding Tasks: MMACTION2 includes algorithms for various tasks like action recognition, action localization, spatio-temporal action detection, skeleton-based action detection, and video retrieval.
- Well-Documented and Tested: Detailed documentation and API references are available, along with comprehensive unit tests to ensure reliability.
Installation
MMACTION2 depends on several underlying software packages including PyTorch, MMCV, MMEngine, and optionally MMDetection and MMPose.
For complete installation instructions, you can refer to the installation guide.
Model Zoo
The project offers a robust model zoo with pretrained models and benchmark results. It supports a wide array of models for action recognition, localization, spatio-temporal detection, and more. The diversity of models allows users to select the best-suited algorithms for their specific video understanding tasks.
Supported Tasks and Models
Some of the supported tasks and their corresponding models include:
- Action Recognition: C3D, TSN, I3D, TSM, SlowFast, VideoMAE, among others.
- Action Localization: BSN, BMN, TCANet.
- Spatio-Temporal Action Detection: ACRN, SlowOnly+Fast R-CNN, and others.
- Skeleton-based Action Recognition: ST-GCN, PoseC3D, CTRGCN, etc.
- Video Retrieval: CLIP4Clip.
Conclusion
MMAction2 is a comprehensive toolbox for video understanding, equipped with state-of-the-art models and a modular architecture that facilitates research and development in the field. With its extensive documentation, easy installation, and wide support for various tasks, it serves as a valuable resource for developers and researchers working on video analysis and understanding projects.