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Hi👋, i'm a PhD candidate (2021.09-now) in Tianjin University, China. My major interests include video understanding, sign language understanding and multi-modal learning. I'd like to let the people benefit more from general computer vision techniques. For more information, please visit www.hulianyu.top. Feel free to contact me via [email protected].

✉ News:

  • We release CorrNet+, an unified model with superior performance on both continuous sign language recognition and sign language translation tasks by using only RGB inputs.

  • We release AdaptSign, a CSLR model powered by frozen pretrained image models with 18.5% & 18.8% WER on phoenix2014, 18.6% & 19.8% WER on phoenix2014-T, 26.7% & 26.3% WER on CSL-Daily.

  • We release DSTA-SLR, which performs sign language recognition (SLR) with pure skeleton inputs but ahcieves comparable accuracy and much faster speed than recognition with RGB inputs.

Anurag's GitHub stats

hulianyu's Projects

adabrowse icon adabrowse

AdaBrowse: Adaptive Video Browser for Efficient Continuous Sign Language Recognition (ACMMM2023 Oral)

adaptsign icon adaptsign

Improving Continuous Sign Language Recognition with Adapted Image Models

comma icon comma

COMMA: Co-Articulated Multi-Modal Learning (AAAI2024)

corrnet icon corrnet

Continuous Sign Language Recognition with Correlation Network (CVPR 2023)

corrnet_plus icon corrnet_plus

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

dsta-slr icon dsta-slr

Dynamic Spatial-Temporal Aggregation for Skeleton-Aware Sign Language Recognition (COLING2024)

minimal-mistakes icon minimal-mistakes

:triangular_ruler: Jekyll theme for building a personal site, blog, project documentation, or portfolio.

sen_cslr icon sen_cslr

Self-Emphasizing Network for Continuous Sign Language Recognition (AAAI2023 Oral)

stgat icon stgat

Skeleton-Based Action Recognition with Local Dynamic Spatial-Temporal Aggregation (Expert Systems with Applications 2023) (Previous name: Spatial Temporal Graph Attention Network for Skeleton-Based Action Recognition)

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