1 code implementation • 10 Jan 2024 • Ronglai Zuo, Fangyun Wei, Brian Mak
Our approach comprises three phases: 1) developing a sign language dictionary encompassing all glosses present in a target sign language dataset; 2) training an isolated sign language recognition model on augmented signs using both conventional classification loss and our novel saliency loss; 3) employing a sliding window approach on the input sign sequence and feeding each sign clip to the well-optimized model for online recognition.
1 code implementation • 9 Jan 2024 • Ronglai Zuo, Fangyun Wei, Zenggui Chen, Brian Mak, Jiaolong Yang, Xin Tong
The objective of this paper is to develop a functional system for translating spoken languages into sign languages, referred to as Spoken2Sign translation.
1 code implementation • CVPR 2023 • Ronglai Zuo, Fangyun Wei, Brian Mak
Sign languages are visual languages which convey information by signers' handshape, facial expression, body movement, and so forth.
Ranked #1 on Sign Language Recognition on WLASL-2000
1 code implementation • 26 Dec 2022 • Ronglai Zuo, Brian Mak
The first task enhances the visual module, which is sensitive to the insufficient training problem, from the perspective of consistency.
Ranked #8 on Sign Language Recognition on CSL-Daily
1 code implementation • 2 Nov 2022 • Yutong Chen, Ronglai Zuo, Fangyun Wei, Yu Wu, Shujie Liu, Brian Mak
RGB videos, however, are raw signals with substantial visual redundancy, leading the encoder to overlook the key information for sign language understanding.
no code implementations • CVPR 2022 • Ronglai Zuo, Brian Mak
The backbone of most deep-learning-based continuous sign language recognition (CSLR) models consists of a visual module, a sequential module, and an alignment module.