The recent success of the generative model shows that leveraging the multi-modal
embedding space can manipulate an image using text information. However, manipulating …

Recently, large pretrained models (eg, BERT, StyleGAN, CLIP) show great knowledge
transfer and generalization capability on various downstream tasks within their domains …

Existing text-guided image manipulation methods aim to modify the appearance of the
image or to edit a few objects in a virtual or simple scenario, which is far from practical …

Image Retrieval with Text Feedback (IRTF) is an emerging research topic where the query
consists of an image and a text expressing a requested attribute modification. The goal is to …

Giving machines the ability to imagine possible new objects or scenes from linguistic
descriptions and produce their realistic renderings is arguably one of the most challenging …

With the emergence of specifically tailored neural architectures that cope with both
modalities, cross-modal language and image processing has attracted increasing attention …

Cross-modal language and image processing is envisaged as a way to improve language
understanding by resorting to visual grounding, but only recently, with the emergence of …

We are interested in image manipulation via natural language text–a task that is extremely
useful for multiple AI applications but requires complex reasoning over multi-modal spaces …