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20222024
most citedMulti-scale temporal network for continuous sign language recognition

7 citations · 12 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2024★ 2 cited

A Chinese Continuous Sign Language Dataset Based on Complex Environments

Qidan Zhu, Jing Li, Fei Yuan +2

The current bottleneck in continuous sign language recognition (CSLR) research lies in the fact that most publicly available datasets are limited to laboratory environments or tele…

cs.CV2024★ 2 cited

Continuous Sign Language Recognition Based on Motor attention mechanism and frame-level Self-distillation

Qidan Zhu, Jing Li, Fei Yuan +1

Changes in facial expression, head movement, body movement and gesture movement are remarkable cues in sign language recognition, and most of the current continuous sign language r…

cs.CV2023

Continuous sign language recognition based on cross-resolution knowledge distillation

Qidan Zhu, Jing Li, Fei Yuan +1

The goal of continuous sign language recognition(CSLR) research is to apply CSLR models as a communication tool in real life, and the real-time requirement of the models is importa…

cs.CV2022

Temporal superimposed crossover module for effective continuous sign language

Qidan Zhu, Jing Li, Fei Yuan +1

The ultimate goal of continuous sign language recognition(CSLR) is to facilitate the communication between special people and normal people, which requires a certain degree of real…

cs.CV2022★ 1 cited

Continuous Sign Language Recognition via Temporal Super-Resolution Network

Qidan Zhu, Jing Li, Fei Yuan +1

Aiming at the problem that the spatial-temporal hierarchical continuous sign language recognition model based on deep learning has a large amount of computation, which limits the r…

cs.CV2022★ 7 cited

Multi-scale temporal network for continuous sign language recognition

Qidan Zhu, Jing Li, Fei Yuan +1

Continuous Sign Language Recognition (CSLR) is a challenging research task due to the lack of accurate annotation on the temporal sequence of sign language data. The recent popular…