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 present a general framework for exemplar-based image translation, which synthesizes a
photo-realistic image from the input in a distinct domain (eg, semantic segmentation mask …

We present the full-resolution correspondence learning for cross-domain images, which aids
image translation. We adopt a hierarchical strategy that uses the correspondence from …

While language-guided image manipulation has made remarkable progress, the challenge
of how to instruct the manipulation process faithfully reflecting human intentions persists. An …

In many applications of computer graphics, art, and design, it is desirable for a user to
provide intuitive non-image input, such as text, sketch, stroke, graph, or layout, and have a …

In this paper, we focus on semantically multi-modal image synthesis (SMIS) task, namely,
generating multi-modal images at the semantic level. Previous work seeks to use multiple …

With the remarkable recent progress on learning deep generative models, it becomes
increasingly interesting to develop models for controllable image synthesis from …

We propose a novel edge guided generative adversarial network with contrastive learning
(ECGAN) for the challenging semantic image synthesis task. Although considerable …

We present a novel method for exemplar-based image translation, called matching
interleaved diffusion models (MIDMs). Most existing methods for this task were formulated as …

We address estimating dense correspondences between two images depicting different but
semantically related scenes. End-to-end trainable deep neural networks incorporating …