Generative adversarial networks: A survey toward private and secure applications
Z Cai, Z ** autoencoder for deep image manipulation
Deep generative models have become increasingly effective at producing realistic images
from randomly sampled seeds, but using such models for controllable manipulation of …
from randomly sampled seeds, but using such models for controllable manipulation of …
Boosting monocular depth estimation models to high-resolution via content-adaptive multi-resolution merging
Neural networks have shown great abilities in estimating depth from a single image.
However, the inferred depth maps are well below one-megapixel resolution and often lack …
However, the inferred depth maps are well below one-megapixel resolution and often lack …
Large scale image completion via co-modulated generative adversarial networks
Numerous task-specific variants of conditional generative adversarial networks have been
developed for image completion. Yet, a serious limitation remains that all existing algorithms …
developed for image completion. Yet, a serious limitation remains that all existing algorithms …