Jun 2, 2020 · We propose a novel semantic boundary detection method based on reinforcement learning for accurate continuous SLR.
Abstract—Sign language recognition (SLR) is a significant and promising technique to facilitate the communication for the hearing-impaired people.
Chengcheng Wei, Jian Zhao, Wengang Zhou, Houqiang Li (2020). Semantic Boundary Detection With Reinforcement Learning for Continuous Sign Language Recognition.
Continuous Sign Language Recognition via Reinforcement ...
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Then, we formulate the semantic boundary detection as a reinforcement learning problem. We define the state as the feature representation of a video segment, ...
4 days ago · The algorithm framework has four parts: key frame extraction, head-hand detection, image partitioning and coding and hand sequence ...
Missing: Reinforcement | Show results with:Reinforcement
Wei, J. Zhao, W. Zhou, and H. Li, “Semantic boundary detection with reinforcement learning for continuous sign language recognition,” IEEE.
This paper proposes to train the Transformer directly on non-differentiable metrics, i.e., word error rate (WER), through RL, and a policy gradient ...
Missing: Boundary Detection
Mar 21, 2023 · “Semantic boundary detection with reinforcement learning for continuous sign language recognition,” TCSVT, vol. 31, no. 3, pp. 1138–1149 ...
This survey aims to provide a comprehensive review of state-of-the-art methods in sign language capturing, recognition, translation and representation.
This work proposes a dynamic pseudo label decoding method to find a reasonable alignment path via dynamic-programming and generates pseudo labels which conform ...