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 …

The performance of existing image dehazing methods is limited by hand-designed features,
such as the dark channel, color disparity and maximum contrast, with complex fusion …

In recent years, computer science has made major advances in understanding drawing
behavior. Artificial intelligence, and more precisely deep learning, has displayed …

Long-Term person re-identification (LT-reID) exposes extreme challenges because of the
longer time gaps between two recording footages where a person is likely to change …

Cloth-Changing person re-identification (CC-ReID) aims at matching the same person
across different locations over a long-duration, eg, over days, and therefore inevitably has …

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 …

Person re-identification (re-id), the process of matching pedestrian images across different
camera views, is an important task in visual surveillance. Substantial development of re-id …

Sketch-based image retrieval (SBIR) is a cross-modal matching problem which is typically
solved by learning a joint embedding space where the semantic content shared between …

Human sketches are unique in being able to capture both the spatial topology of a visual
object, as well as its subtle appearance details. Fine-grained sketch-based image retrieval …

Free-hand sketch-based image retrieval (SBIR) is a specific cross-view retrieval task, in
which queries are abstract and ambiguous sketches while the retrieval database is formed …