Publications by authors named "Le Hui"

In zero-shot learning (ZSL), attribute knowledge plays a vital role in transferring knowledge from seen classes to unseen classes. However, most existing ZSL methods learn biased attribute knowledge, which usually results in biased attribute prediction and a decline in zero-shot recognition performance. To solve this problem and learn unbiased attribute knowledge, we propose a visual attribute Transformer for zero-shot recognition (ZS-VAT), which is an effective and interpretable Transformer designed specifically for ZSL.

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Learning robust feature matching between the template and search area is crucial for 3-D Siamese tracking. The core of Siamese feature matching is how to assign high feature similarity to the corresponding points between the template and the search area for precise object localization. In this article, we propose a novel point cloud registration-driven Siamese tracking framework, with the intuition that spatially aligned corresponding points (via 3-D registration) tend to achieve consistent feature representations.

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Point cloud based retrieval for place recognition is still a challenging problem since the drastic appearance changes of scenes due to seasonal or artificial changes in the environments. Existing deep learning based global descriptors for the retrieval task usually consume a large amount of computational resources ( e.g .

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A novel hybrid nanostructure, that is a Ag nanoparticle decorated LaF(3):Yb(3+)/Ln(3+)@SiO(2) nanosphere (Ln=Er, Tm), was constructed by a facile strategy, and characterized by XRD, TEM, FTIR, XPS and UV-vis-NIR absorption. Obvious spectral broadening and red-shift on the surface plasmon resonance were obtained by adjusting the size and configuration of Ag nanoparticles. Effective upconversion luminescence enhancements for Er(3+) and Tm(3+) containing samples were obtained.

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A single nucleotide polymorphism in the dog CYP1A2 gene causes these animals to be CYP1A2 deficient (i.e., lack functional CYP1A2 enzyme activity).

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