Data scarcity is a major challenge when training deep learning (DL) models. DL demands a
large amount of data to achieve exceptional performance. Unfortunately, many applications …

Generative adversarial networks (GANs), a novel framework for training generative models
in an adversarial setup, have attracted significant attention in recent years. The two …

Despite the significant progress of conditional image generation, it remains difficult to
synthesize a ground-view panorama image from a top-view aerial image. Among the core …

Text-to-image synthesis is an attractive but challenging task that aims to generate a photo-
realistic and semantic consistent image from a specific text description. The images …

Abstract Controllable Image Synthesis (CIS) is a methodology that allows users to generate
desired images or manipulate specific attributes of images by providing precise input …

Text-to-image generation has attracted significant interest from researchers and practitioners
in recent years due to its widespread and diverse applications across various industries …

Text-based person search (TBPS) aims to retrieve the images of the target person from a
large image gallery based on a given natural language description. Existing methods are …

Text-guided image inpainting aims to generate corrupted image patches and obtain a
plausible image based on textual descriptions, considering the relationship between textual …

Leveraging the abundant knowledge learned from pre-trained multi-modal models like CLIP
has recently proved to be effective for text-guided image editing. Though convincing results …

Generating high-quality images from text remains a challenge in visual-language
understanding, with text-image consistency being a major concern. Particularly, the most …