Estimating the pose of animals can facilitate the understanding of animal motion which is fundamental in disciplines such as biomechanics, neuroscience, ethology, robotics and the entertainment industry.
Ranked #1 on Animal Pose Estimation on StanfordExtra
We incorporate this model within a dual stream network integrating pose embeddings derived from MVV and a forward kinematic solve of the IMU data.
Ranked #7 on 3D Human Pose Estimation on Total Capture
We present a method to continuously blend between multiple facial performances of an actor, which can contain different facial expressions or emotional states.