no code implementations • 2 Jun 2023 • JinMan Park, Francois Barnard, Saad Hossain, Sirisha Rambhatla, Paul Fieguth
Unsupervised domain adaptation (UDA) aims to bridge the gap between source and target domains in the absence of target domain labels using two main techniques: input-level alignment (such as generative modeling and stylization) and feature-level alignment (which matches the distribution of the feature maps, e. g. gradient reversal layers).
no code implementations • 1 Jun 2023 • Kimathi Kaai, Saad Hossain, Sirisha Rambhatla
This requires a class to be expressed in multiple domains for the learning algorithm to break the spurious correlations between domain and class.
no code implementations • 9 Jun 2022 • JinMan Park, Kimathi Kaai, Saad Hossain, Norikatsu Sumi, Sirisha Rambhatla, Paul Fieguth
Egocentric 3D human pose estimation (HPE) from images is challenging due to severe self-occlusions and strong distortion introduced by the fish-eye view from the head mounted camera.