Search Results for author:
Found 3 papers, 1 papers with code
Quality Map Fusion for Adversarial Learning
Generative adversarial models that capture salient low-level features which convey visual information in correlation with the human visual system (HVS) still suffer from perceptible image degradations.
Ortho-Shot: Low Displacement Rank Regularization with Data Augmentation for Few-Shot Learning
In few-shot classification, the primary goal is to learn representations from a few samples that generalize well for novel classes.
Quality Guided Sketch-to-Photo Image Synthesis
We incorporate a hybrid discriminator which performs attribute classification of multiple target attributes, a quality guided encoder that minimizes the perceptual dissimilarity of the latent space embedding of the synthesized and real image at different layers in the network and an identity preserving network that maintains the identity of the synthesised image throughout the training process.
