Heterogeneous Face Recognition (HFR) is a task that matches faces across two different domains such as visible light (VIS), near-infrared (NIR), or the sketch domain. Due to lack of databases, HFR methods usually exploit pre-trained features on large-scale visual database contain general facial information. However, these cause performance degradation due texture discrepancy with With this moti...

Deep neural networks have achieved great success on many visual recognition tasks. However, training data with a long-tailed distribution dramatically degenerates the performance of models. In order to relieve this imbalance problem, an effective Long-Tailed Visual Recognition (LTVR) framework is proposed based learned balance and robust features under circumstances. framework, plug-and-play At...

Named entity recognition can deeply explore semantic features and enhance the ability of vector representation text data. This paper proposes a named method based on multi-head attention to aim at problem fuzzy lexical boundary in Chinese recognition. Firstly, Word2vec is used extract word vectors, HMM ALBERT character Feedforward-attention mechanism fuse three then fused vectors remove by BiLS...