Image synthesis is a process of converting the input text, sketch, or other sources, ie, another
image or mask, into an image. It is an important problem in the computer vision field, where it …

In this paper, we leverage CLIP for zero-shot sketch based image retrieval (ZS-SBIR). We
are largely inspired by recent advances on foundation models and the unparalleled …

Fine-grained image analysis (FGIA) is a longstanding and fundamental problem in computer
vision and pattern recognition, and underpins a diverse set of real-world applications. The …

This paper unravels the potential of sketches for diffusion models addressing the deceptive
promise of direct sketch control in generative AI. We importantly democratise the process …

Heterogeneous face recognition (HFR) refers to matching face imagery across different
domains. It has received much interest from the research community as a result of its …

The problem of domain generalization is to learn from multiple training domains, and extract
a domain-agnostic model that can then be applied to an unseen domain. Domain …

Given an abstract, deformed, ordinary sketch from untrained amateurs like you and me, this
paper turns it into a photorealistic image-just like those shown in Fig. 1 (a), all non-cherry …

In this paper we propose a novel abstraction-aware sketch-based image retrieval framework
capable of handling sketch abstraction at varied levels. Prior works had mainly focused on …

This paper studies the problem of zero-short sketch-based image retrieval (ZS-SBIR),
however with two significant differentiators to prior art (i) we tackle all variants (inter …

Sketches are highly expressive, inherently capturing subjective and fine-grained visual
cues. The exploration of such innate properties of human sketches has, however, been …