Test-TimePersonalizationwithaTransformerfor HumanPoseEstimation

While there is a significant advancement in human pose estimation, it is still very challenging for a model togeneralize todifferent unknownenvironments andunseen persons. Instead of using a fixed model for every test case, we adapt our pose estimator during test time to exploit person-specific information.