Sign language is a form of visual communication employing hand gestures, body
movements, and facial expressions. The growing prevalence of hearing impairment has …

The co-occurrence signals (eg, hand shape, facial expression, and lip pattern) play a critical
role in Continuous Sign Language Recognition (CSLR). Compared to RGB data, skeleton …

Abstract The task of Visual Question Answering (VQA) is known to be plagued by the issue
of VQA models exploiting biases within the dataset to make its final prediction. Various …

The recent advancements in computer vision and deep learning have led to promising
progress in various motion detection and gesture recognition methods. Thriving efforts in the …

The goal of this work is to develop self-sufficient framework for Continuous Sign Language
Recognition (CSLR) that addresses key issues of sign language recognition. These include …

Growing research in sign language recognition, generation, and translation AI has been
accompanied by calls for ethical development of such technologies. While these works are …

We present a novel data-efficient semi-supervised framework to improve the generalization
of image captioning models. Constructing a large-scale labeled image captioning dataset is …

The objective of this work is the effective extraction of spatial and dynamic features for
Continuous Sign Language Recognition (CSLR). To accomplish this, we utilise a two …

Video Temporal Grounding (VTG) aims to identify visual frames in a video clip that match
text queries. Recent studies in VTG employ cross-attention to correlate visual frames and …

In this paper, we propose a new method to enhance compositional understanding in pre-
trained vision and language models (VLMs) without sacrificing performance in zero-shot …