activity
20162023
most citedAmerican Sign Language fingerspelling recognition in the wild

5 citations · 20 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2023★ 4 cited

Self-Supervised Video Transformers for Isolated Sign Language Recognition

Marcelo Sandoval-Castaneda, Yanhong Li, Diane Brentari +2

This paper presents an in-depth analysis of various self-supervision methods for isolated sign language recognition (ISLR). We consider four recently introduced transformer-based a…

cs.CV2022★ 4 cited

Open-Domain Sign Language Translation Learned from Online Video

Bowen Shi, Diane Brentari, Greg Shakhnarovich +1

Existing work on sign language translation - that is, translation from sign language videos into sentences in a written language - has focused mainly on (1) data collected in a con…

cs.CV2022

Searching for fingerspelled content in American Sign Language

Bowen Shi, Diane Brentari, Greg Shakhnarovich +1

Natural language processing for sign language video - including tasks like recognition, translation, and search - is crucial for making artificial intelligence technologies accessi…

cs.CV2021

Fingerspelling Detection in American Sign Language

Bowen Shi, Diane Brentari, Greg Shakhnarovich +1

Fingerspelling, in which words are signed letter by letter, is an important component of American Sign Language. Most previous work on automatic fingerspelling recognition has assu…

cs.CV2019★ 4 cited

Fingerspelling recognition in the wild with iterative visual attention

Bowen Shi, Aurora Martinez Del Rio, Jonathan Keane +3

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 fi…

cs.CV2018★ 5 cited

American Sign Language fingerspelling recognition in the wild

Bowen Shi, Aurora Martinez Del Rio, Jonathan Keane +4

We address the problem of American Sign Language fingerspelling recognition in the wild, using videos collected from websites. We introduce the largest data set available so far fo…

cs.CL2016★ 3 cited

Lexicon-Free Fingerspelling Recognition from Video: Data, Models, and Signer Adaptation

Taehwan Kim, Jonathan Keane, Weiran Wang +5

We study the problem of recognizing video sequences of fingerspelled letters in American Sign Language (ASL). Fingerspelling comprises a significant but relatively understudied par…