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 …

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 …

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 …

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 …

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

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 …

We present the Sketchy database, the first large-scale collection of sketch-photo pairs. We
ask crowd workers to sketch particular photographic objects sampled from 125 categories …

We tackle the task of image retrieval with text feedback, where a reference image and
modifier text are combined to identify the desired target image. We focus on designing an …

Synthesizing realistic images from human drawn sketches is a challenging problem in
computer graphics and vision. Existing approaches either need exact edge maps, or rely on …