As information exists in various modalities in real world, effective interaction and fusion
among multimodal information plays a key role for the creation and perception of multimodal …

The creation of an image from another and from different types of data including text, scene
graph, and object layout, is one of the very challenging tasks in computer vision. In addition …

Image-to-image translation (I2I) aims to transfer images from a source domain to a target
domain while preserving the content representations. I2I has drawn increasing attention and …

Despite the great success of GANs in images translation with different conditioned inputs
such as semantic segmentation and edge map, generating high-fidelity images with …

Exemplar-based image translation establishes dense correspondences between a
conditional input and an exemplar (from two different domains) for leveraging detailed …

We propose a novel Generative Adversarial Network (XingGAN or CrossingGAN) for person
image generation tasks, ie, translating the pose of a given person to a desired one. The …

Deep generative models have achieved conspicuous progress in realistic image synthesis
with multifarious conditional inputs, while generating diverse yet high-fidelity images …

State-of-the-art methods in the image-to-image translation are capable of learning a
mapping from a source domain to a target domain with unpaired image data. Though the …

Pose-guided person image generation is to transform a source person image to a target
pose. This task requires spatial manipulations of source data. However, Convolutional …

In this paper, we introduce a large Multi-Attribute and Language Search dataset for text-
based person retrieval, called MALS, and explore the feasibility of performing pre-training on …