Most existing image dehazing methods based learning are less able to perform well real hazy images. An important reason is that they trained on synthetic images whose distribution different from To relieve this issue, paper proposes a new scene generation model domain adaptation, which uses variational autoencoder encode the pairs and into latent space adapt. The guide learn mapping of clear im...

We present a 2-step optimal transport approach that performs mapping from source distribution to target distribution. Here, the has particularity new classes not in domain. The first step of aims at rejecting samples issued these using an plan. second solves (class ratio) shift still as problem. develop dual solve optimization problem involved each and we prove our results outperform recent sta...

A pre-trained language model, BERT, has brought significant performance improvements across a range of natural processing tasks. Since the model is trained on large corpus diverse topics, it shows robust for domain shift problems in which data distributions at training (source data) and testing (target differ while sharing similarities. Despite its great compared to previous models, still suffe...