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20222024
most citedContinuous Sign Language Recognition with Correlation Network

7 citations · 22 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV20242 cited

CorrNet+: Sign Language Recognition and Translation via Spatial-Temporal Correlation

Lianyu Hu, Wei Feng, Liqing Gao +2

In sign language, the conveyance of human body trajectories predominantly relies upon the coordinated movements of hands and facial expressions across successive frames. Despite th…

cs.CV20243 cited

Improving Continuous Sign Language Recognition with Adapted Image Models

Lianyu Hu, Tongkai Shi, Liqing Gao +2

The increase of web-scale weakly labelled image-text pairs have greatly facilitated the development of large-scale vision-language models (e.g., CLIP), which have shown impressive…

cs.CV2024

Dynamic Spatial-Temporal Aggregation for Skeleton-Aware Sign Language Recognition

Lianyu Hu, Liqing Gao, Zekang Liu +1

Skeleton-aware sign language recognition (SLR) has gained popularity due to its ability to remain unaffected by background information and its lower computational requirements. Cur…

cs.CV2023

COMMA: Co-Articulated Multi-Modal Learning

Lianyu Hu, Liqing Gao, Zekang Liu +2

Pretrained large-scale vision-language models such as CLIP have demonstrated excellent generalizability over a series of downstream tasks. However, they are sensitive to the variat…

cs.CV20233 cited

AdaBrowse: Adaptive Video Browser for Efficient Continuous Sign Language Recognition

Lianyu Hu, Liqing Gao, Zekang Liu +2

Raw videos have been proven to own considerable feature redundancy where in many cases only a portion of frames can already meet the requirements for accurate recognition. In this…

cs.CV20237 cited

Continuous Sign Language Recognition with Correlation Network

Lianyu Hu, Liqing Gao, Zekang Liu +1

Human body trajectories are a salient cue to identify actions in the video. Such body trajectories are mainly conveyed by hands and face across consecutive frames in sign language.…