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 …

The content based image retrieval aims to find the similar images from a large scale dataset
against a query image. Generally, the similarity between the representative features of the …

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 …

Sketching enables many exciting applications, notably, image retrieval. The fear-to-sketch
problem (ie," I can't sketch") has however proven to be fatal for its widespread adoption. This …

Remote sensing image retrieval (RSIR) aims to search and retrieve the images of interest
from a large remote sensing image archive, which has remained to be a hot topic over the …

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 …

In this work, we present a novel multi-scale feature fusion network (M-FFN) for image
captioning task to incorporate discriminative features and scene contextual information of an …

Sentiment analysis of social media data is crucial to understand people's position, attitude,
and opinion toward a certain event, which has many applications such as election prediction …