Reviews: Dual Adversarial Semantics-Consistent Network for Generalized Zero-Shot Learning

The primary contribution of the paper is the dual-GAN structure with semantics-consistency and visual-consistency loss. The paper has novel components (although it is close to [7], see below). The paper shows that their model performs better than the existing methods on GZSL benchmark datasets. To better understand the individual contribution of these losses, the paper gives an ablation study in Table 3. However, it should also include results of ablation study on CUB and SUN datasets in the main paper.