Biometric recognition technology has made significant advances over the last decade and is
now used across a number of services and applications. However, this widespread …

The multimodal task of Visual Question Answering (VQA) encompassing elements of
Computer Vision (CV) and Natural Language Processing (NLP), aims to generate answers …

While an important problem in the vision community is to design algorithms that can
automatically caption images, few publicly-available datasets for algorithm development …

Individuals suffering from visual impairments and blindness encounter difficulties in moving
independently and overcoming various problems in their routine lives. As a solution, artificial …

Object hallucination poses a significant challenge in vision-language (VL) models, often
leading to the generation of nonsensical or unfaithful responses with non-existent objects …

Visual question answering is the task of answering questions about images. We introduce
the VizWiz-VQA-Grounding dataset, the first dataset that visually grounds answers to visual …

Large language models (LLMs) trained on real-world data can inadvertently reflect harmful
societal biases, particularly toward historically marginalized communities. While previous …

The emergence of camera-based assistive technologies has empowered people with visual
impairments (VIP) to obtain independence in their daily lives. Popular services feature …

Deep learning methods have achieved remarkable success in fine-grained visual
categorization. Such successful categorization at sub-ordinate level, eg, different animal or …

Story visualization (SV) is a challenging text-to-image generation task for the difficulty of not
only rendering visual details from the text descriptions but also encoding a longterm context …