Abstract “Art is the lie that enables us to realize the truth.”–Pablo Picasso. For centuries,
humans have dedicated themselves to producing arts to convey their imagination. The …

The metaverse, enormous virtual-physical cyberspace, has brought unprecedented
opportunities for artists to blend every corner of our physical surroundings with digital …

Current text recognition systems, including those for handwritten scripts and scene text, have
relied heavily on image synthesis and augmentation, since it is difficult to realize real-world …

Automatic font generation remains a challenging research issue due to the large amounts of
characters with complicated structures. Typically, only a few samples can serve as the …

Existing handwritten text generation methods often require more than ten handwriting
samples as style references. However, in practical applications, users tend to prefer a …

Handwriting synthesis, the task of automatically generating realistic images of handwritten
text, has gained increasing attention in recent years, both as a challenge in itself, as well as …

Handwritten Text Recognition has achieved an impressive performance in public
benchmarks. However, due to the high inter-and intra-class variability between handwriting …

Recently, with the rapid advancements of generative models, the field of visual text
generation has witnessed significant progress. However, it is still challenging to render high …

We present a novel approach for disentangling the content of a text image from all aspects of
its appearance. The appearance representation we derive can then be applied to new …

We propose a novel transformer-based styled handwritten text image generation approach,
HWT, that strives to learn both style-content entanglement as well as global and local style …