Fingerspelling recognition in the wild with iterative visual attention

ICCV 2019 Bowen ShiAurora Martinez Del RioJonathan KeaneDiane BrentariGreg ShakhnarovichKaren Livescu

Sign language recognition is a challenging gesture sequence recognition problem, characterized by quick and highly coarticulated motion. In this paper we focus on recognition of fingerspelling sequences in American Sign Language (ASL) videos collected in the wild, mainly from YouTube and Deaf social media... (read more)

PDF Abstract ICCV 2019 PDF ICCV 2019 Abstract

Code


No code implementations yet. Submit your code now

Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods used in the Paper


METHOD TYPE
🤖 No Methods Found Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet