Recently text-guided scalable vector graphics (SVGs) synthesis has shown promise in
domains such as iconography and sketch. However existing text-to-SVG generation …

The pre-trained text-image discriminative models, such as CLIP, has been explored for open-
vocabulary semantic segmentation with unsatisfactory results due to the loss of crucial …

We propose SketchINR to advance the representation of vector sketches with implicit neural
models. A variable length vector sketch is compressed into a latent space of fixed dimension …

Score distillation sampling (SDS) has proven to be an important tool, enabling the use of
large-scale diffusion priors for tasks operating in data-poor domains. Unfortunately, SDS has …

Abstract We introduce Posterior Distillation Sampling (PDS) a novel optimization method for
parametric image editing based on diffusion models. Existing optimization-based methods …

Vector graphics are widely used in digital art and highly favored by designers due to their
scalability and layer-wise properties. However, the process of creating and editing vector …

Clipart, a pre-made graphic art form, offers a convenient and efficient way of illustrating
visual content. Traditional workflows to convert static clipart images into motion sequences …

Sketching serves as a versatile tool for externalizing ideas, enabling rapid exploration and
visual communication that spans various disciplines. While artificial systems have driven …

In this paper we explore a novel challenging generation task ie Handwritten Mathematical
Expression Generation (HMEG) from symbolic sequences. Since symbolic sequences are …

The unprecedented advancements in Large Language Models (LLMs) have profoundly
impacted natural language processing but have yet to fully embrace the realm of scalable …