Unsupervised Domain Adaptation with Multiple Domain Discriminators and Adaptive Self-Training

no code implementations • 27 Apr 2020 • Teo Spadotto, Marco Toldo, Umberto Michieli, Pietro Zanuttigh

We introduce a novel UDA framework where a standard supervised loss on labeled synthetic data is supported by an adversarial module and a self-training strategy aiming at aligning the two domain distributions.

Segmentation Semantic Segmentation +1