This project is designed to display how we can utilize deep learning methods for Sports Data Analytics.

[NeurIPS 2022 Spotlight] VideoMAE for Action Detection

[NeurIPS'22] VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training

EchoCardMAE: Video Masked Auto-Encoders Customized for Echocardiography

Real‑time crime detection system using VideoMAE, Flask, async camera streaming, alert snapshots, and email notifications.

Efficient video action recognition using hybrid techniques: combining ORB, SIFT, and deep models like VideoMAE and (2+1)D Conv to reduce data size while maintaining performance.

A Computer Vision Project for the AAI3001 module