2019
Multi-objects Generation with Amortized Structural Regularization
NeurIPS 2019poster
Deep generative models (DGMs) have shown promise in image generation. However, most of the existing methods learn a model by simply optimizing a divergence between the marginal distributions of the model and the data, and often fail to capture rich structures, such as attributes of objects and their…