Deep video understanding is one of the most challenging tasks in computer vision. With the rise of computing power and the amount of video data on the internet, the demand for new-age machine learning models and tools continues to grow. As per Stanford University, technologies used to develop object detection from videos are maturing rapidly.

Facebook AI recently unveiled a new deep learning library for video understanding called PyTorchVideo. The source code is available on GitHub.

With PyTorchVideo, Facebook aims to help researchers develop cutting-edge machine learning models and tools to enhance video understanding capabilities, alongside providing a unified repository of reproducible and efficient video understanding components for research and production applications.

In addition to this,  Facebook is looking to standardise video-focused libraries that serve various video use cases in one place.“This has created a barrier for developers looking to work with videos for the first time,” said Facebook AI, stating that lack of standardisation makes it difficult to collaborate and spur innovation.

In the coming months, Facebook will improve the PyTorchVideo library to enable and support more groundbreaking research in video understanding. “We welcome contributions from the entire community. All our efforts will be directed at supporting the rich open-source community committed to pushing the boundaries of video research,” said Facebook.

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