The problem of human activity recognition from mobile sensor data applies to multiple domains, such as health monitoring, personal fitness, daily life logging, and senior care.
AMD is a metric that quantifies how close the whole generated samples are to the ground truth.
Ranked #1 on Trajectory Prediction on Stanford Drone (ADE (in world coordinates) metric)
We propose Skeleton-Graph, a deep spatio-temporal graph CNN model that predicts the future 3D skeleton poses in a single pass from the 2D ones.
Ranked #1 on Trajectory Prediction on PROX
Also, we show empirically and theoretically that IENs lead to a greater variance reduction in comparison with other similar approaches such as dropout and maxout.
Better machine understanding of pedestrian behaviors enables faster progress in modeling interactions between agents such as autonomous vehicles and humans.
Ranked #3 on Trajectory Prediction on ETH