Papers › TCNet: Continuous Sign Language Recognition from Trajectories and Correlated Regions
TCNet: Continuous Sign Language Recognition from Trajectories and Correlated Regions
Hui Lu, Albert Ali Salah, Ronald Poppe
A key challenge in continuous sign language recognition (CSLR) is to efficiently capture long-range spatial interactions over time from the video input. To address this challenge, we propose TCNet, a hybrid network that effectively models spatio-temporal information from Trajectories and Correlated regions. TCNet's trajectory module transforms frames into aligned trajectories composed of continuous visual tokens. In addition, for a query token, self-attention is learned along the trajectory. As such, our network can also focus on fine-grained spatio-temporal patterns, such as finger movements, of a specific region in motion. TCNet's correlation module uses a novel dynamic attention mechanism that filters out irrelevant frame regions. Additionally, it assigns dynamic key-value tokens from correlated regions to each query. Both innovations significantly reduce the computation cost and memory. We perform experiments on four large-scale datasets: PHOENIX14, PHOENIX14-T, CSL, and CSL-Daily, respectively. Our results demonstrate that TCNet consistently achieves state-of-the-art performance. For example, we improve over the previous state-of-the-art by 1.5% and 1.0% word error rate on PHOENIX14 and PHOENIX14-T, respectively.
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Sign Language Recognition | CSL-Daily | TCNet | Word Error Rate (WER) | 29.3 | #8 of 14 | Archive leaderboard | report |
| Sign Language Recognition | RWTH-PHOENIX-Weather 2014 | TCNet | Word Error Rate (WER) | 18.9 | #5 of 22 | Archive leaderboard | report |
| Sign Language Recognition | RWTH-PHOENIX-Weather 2014 T | TCNet | Word Error Rate (WER) | 19.4 | #3 of 15 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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