Efficient rendering of photo‐realistic virtual worlds is a long standing effort of computer
graphics. Modern graphics techniques have succeeded in synthesizing photo‐realistic …

We propose spatially-adaptive normalization, a simple but effective layer for synthesizing
photorealistic images given an input semantic layout. Previous methods directly feed the …

Object class detection, also known as category-level object detection, has become one of
the most focused areas in computer vision in the new century. This article attempts to …

We present a new method for synthesizing high-resolution photo-realistic images from
semantic label maps using conditional generative adversarial networks (conditional GANs) …

Recently, there have been several promising methods to generate realistic imagery from
deep convolutional networks. These methods sidestep the traditional computer graphics …

We propose an automatic method to infer high dynamic range illumination from a single,
limited field-of-view, low dynamic range photograph of an indoor scene. In contrast to …

Despite the recent success of GANs in synthesizing images conditioned on inputs such as a
user sketch, text, or semantic labels, manipulating the high-level attributes of an existing …

Automatic image synthesis research has been rapidly growing with deep networks getting
more and more expressive. In the last couple of years, we have observed images of digits …

In this paper, we investigate deep image synthesis guided by sketch, color, and texture.
Previous image synthesis methods can be controlled by sketch and color strokes but we are …

Scene categorization is a fundamental problem in computer vision. However, scene
understanding research has been constrained by the limited scope of currently-used …