Deep learning, which is a subfield of machine learning, has opened a new era for the
development of neural networks. The auto-encoder is a key component of deep structure …

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 …

Sentence embeddings are an important component of many natural language processing
(NLP) systems. Like word embeddings, sentence embeddings are typically learned on large …

A family of loss functions built on pair-based computation have been proposed in the
literature which provide a myriad of solutions for deep metric learning. In this pa-per, we …

This paper tackles the automatic colorization task of a sketch image given an already-
colored reference image. Colorizing a sketch image is in high demand in comics, animation …

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 …

Mining informative negative instances are of central importance to deep metric learning
(DML). However, the hard-mining ability of existing DML methods is intrinsically limited by …

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

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 …

Image search with text feedback has promising impacts in various real-world applications,
such as e-commerce and internet search. Given a reference image and text feedback from …