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 …

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 …

Human sketch has already proved its worth in various visual understanding tasks (eg,
retrieval, segmentation, image-captioning, etc). In this paper, we reveal a new trait of …

This paper studies the problem of 2D sketch to 3D shape retrieval, but with a focus on
democratising the process. We would like this democratisation to happen on two fronts:(i) to …

In this paper, we extend scene understanding to include that of human sketch. The result is a
complete trilogy of scene representation from three diverse and complementary modalities …

Two primary input modalities prevail in image retrieval: sketch and text. While text is widely
used for inter-category retrieval tasks, sketches have been established as the sole preferred …

This paper, for the first time, explores text-to-image diffusion models for Zero-Shot Sketch-
based Image Retrieval (ZS-SBIR). We highlight a pivotal discovery: the capacity of text-to …

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 …

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 …