most citedSign2GPT: Leveraging Large Language Models for Gloss-Free Sign Language Translation

5 citations · 5 across the 3 of their papers we have counts for

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cs.CV2025

SignRep: Enhancing Self-Supervised Sign Representations

Ryan Wong, Necati Cihan Camgoz, Richard Bowden

Sign language representation learning presents unique challenges due to the complex spatio-temporal nature of signs and the scarcity of labeled datasets. Existing methods often rel…

cs.CV2024

Modelling the Distribution of Human Motion for Sign Language Assessment

Oliver Cory, Ozge Mercanoglu Sincan, Matthew Vowels +7

Sign Language Assessment (SLA) tools are useful to aid in language learning and are underdeveloped. Previous work has focused on isolated signs or comparison against a single refer…

cs.CV20245 cited

Sign2GPT: Leveraging Large Language Models for Gloss-Free Sign Language Translation

Ryan Wong, Necati Cihan Camgoz, Richard Bowden

Automatic Sign Language Translation requires the integration of both computer vision and natural language processing to effectively bridge the communication gap between sign and sp…

cs.CV2024

Giving a Hand to Diffusion Models: a Two-Stage Approach to Improving Conditional Human Image Generation

Anton Pelykh, Ozge Mercanoglu Sincan, Richard Bowden

Recent years have seen significant progress in human image generation, particularly with the advancements in diffusion models. However, existing diffusion methods encounter challen…

cs.CV2024

Spotter+GPT: Turning Sign Spottings into Sentences with LLMs

Ozge Mercanoglu Sincan, Richard Bowden

Sign Language Translation (SLT) is a challenging task that aims to generate spoken language sentences from sign language videos. In this paper, we introduce a lightweight, modular…