We introduce DatasetGAN: an automatic procedure to generate massive datasets of high-
quality semantically segmented images requiring minimal human effort. Current deep …

Generative adversarial networks (GANs) have recently found applications in image editing.
However, most GAN-based image editing methods often require large-scale datasets with …

Training deep networks with limited labeled data while achieving a strong generalization
ability is key in the quest to reduce human annotation efforts. This is the goal of semi …

Existing computer vision systems can compete with humans in understanding the visible
parts of objects, but still fall far short of humans when it comes to depicting the invisible parts …

Panoptic image segmentation is the computer vision task of finding groups of pixels in an
image and assigning semantic classes and object instance identifiers to them. Research in …

We introduce pix2gestalt, a framework for zero-shot amodal segmentation, which learns to
estimate the shape and appearance of whole objects that are only partially visible behind …

We consider the challenging problem of outdoor lighting estimation for the goal of
photorealistic virtual object insertion into photographs. Existing works on outdoor lighting …