Github Sizhean Mars Contribute to sizhean mars development by creating an account on github. Sizhe an, yin li, and umit ogras. accepted in neurips 2022 datasets & benchmarks track [dataset] [code] [openreview] mars: mmwave based assistive rehabilitation system for smart healthcare. sizhe an and umit ogras. codes, esweek 2021, oral presentation [paper] [code and data].
Github Sizhean Mars We propose a millimeter wave (mmwave) based assistive rehabilitation system (mars) for motor disorders to address these challenges. mars provides a low cost solution with a competitive object localization and detection accuracy. Contribute to sizhean mars development by creating an account on github. Contribute to sizhean mars development by creating an account on github. Contribute to sizhean mars development by creating an account on github.
About Sizhe An Research Scientist Contribute to sizhean mars development by creating an account on github. Contribute to sizhean mars development by creating an account on github. Contribute to sizhean mars development by creating an account on github. To bridge the gap, we present mri, a multi modal 3d human pose estimation dataset with mmwave, rgb d, and inertial sensors. our dataset consists of over 160k synchronized frames from 20 subjects performing rehabilitation exercises and supports the benchmarks of hpe and action detection. Download the mars behavior dataset here! included in this dataset are approximately 14 hours of top view video of pairs of interacting mice, accompanied by mars pose estimator output (keypoint locations, bounding boxes, and derived features) and manual frame by frame annotations. This section evaluates the optimized temporal model against the state of the art spatial model mars on the dataset used in mars, underlining the benefits of temporal dynamics for human pose estimation.
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