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- Yuan Yan TangSuggested from co-authorship
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Works290 from public data
- Multiscale patch-based contrast measure for small infrared target detection780
Experimental results on three sequences demonstrate that the proposed small target detection method can not only suppress background clutter effectively even if with strong noise interference, but also detect targets accurately with low false alarm rate and high speed.
- Segmentation of retinal blood vessels using the radial projection and semi-supervised approach402
A novel scheme of extracting the retinal vessels based on the radial projection and semi-supervised method that can achieve improved detection of thin vessels and decrease false detection of vessels in pathological regions compared to rival solutions is presented.
- Hierarchical Bilinear Pooling for Fine-Grained Visual Recognition353
A cross-layer bilinear pooling approach is proposed to capture the inter-layer part feature relations, which results in superior performance compared with other bilinears pooling based approaches.
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- FREE: Feature Refinement for Generalized Zero-Shot Learning229
A feature refinement module that in-corporates semantic→visual mapping into a unified generative model to refine the visual features of seen and unseen class samples, and a self-adaptive margin center loss (SAMC-loss) that cooperates with a semantic cycle-consistency loss to guide FR to learn class- and semantically-relevant representations.
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- TransZero: Attribute-Guided Transformer for Zero-Shot Learning206
This paper proposes an attribute-guided Transformer network to learn the attribute localization for discriminative visual-semantic embedding representations in ZSL, termed TransZero, which achieves a new state-of-the-art on three ZSL benchmarks.
- Shape matching and classification using height functions193
A novel shape descriptor for matching and recognizing 2D object silhouettes that is not only invariant to geometric transformations such as translation, rotation and scaling but also insensitive to nonlinear deformations due to noise and occlusion is proposed.
- Robust face recognition via occlusion dictionary learning180
The proposed novel structured dictionary learning method achieves better results than the existing sparse representation based face recognition methods, especially in dealing with large region contiguous occlusion and severe illumination variation, while the computational cost is much lower.
- MSDN: Mutually Semantic Distillation Network for Zero-Shot Learning163
A Mutually Semantic Distillation Network (MSDN) is proposed, which progressively distills the intrinsic semantic representations between visual and attribute features for ZSL, leading to new state-of-the-art performances on three popular challenging benchmarks.
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- Efficient single image dehazing and denoising: An efficient multi-scale correlated wavelet approach136
This paper presents an efficient multi-scale correlated wavelet approach to solve the image dehazing and denoising problem in the frequency domain and finds a generic regularity in nature images that the haze is typically distributed in the low frequency spectrum of its multi- scale wavelet decomposition.
- Connected Component Model for Multi-Object Tracking133
This paper shows that the relation between associations of two observations is the equivalence relation in the data association problem, based on the spatial-temporal constraint that the trajectories of different objects must be disjoint, and develops a connected component model (CCM), which can efficiently obtain the global solution of the MDA problem for multi-object tracking by optimizing a sequence of independent data association subproblems.
- Multi-view low-rank dictionary learning for image classification131
This paper provides a multi-view dictionary low-rank regularization term to solve the noise problem, and designs a structural incoherence constraint for multi-View DL, such that redundancy among dictionaries of different views can be reduced.
- Automatic kidney segmentation in ultrasound images using subsequent boundary distance regression and pixelwise classification networks121
This study first uses deep neural networks pre-trained for classification of natural images to extract high-level image features from US images to segment the kidneys automatically, and adopts a data-augmentation method based on kidney shape registration to generate enriched training data from a small number of US images.
- Writer identification of Chinese handwriting documents using hidden Markov tree model120
A novel method based on hidden Markov tree (HMT) model in wavelet domain for off-line, text-independent writer identification of Chinese handwriting documents is presented and experiments show this HMT method not only achieves better identification results but also greatly reduces the elapsed time on computation.
- A new weighted mean filter with a two-phase detector for removing impulse noise110
Experimental results show that the proposed method outperforms all the tested state-of-the-art denoising methods with respect to the visual effects and quantitative measure results.
- Skeletonization of ribbon-like shapes based on a new wavelet function108
Experimental results show that the proposed wavelet-based scheme is capable of extracting exactly the skeleton of the Ribbon-like shape with different width as well as different gray-levels, and is robust against noise and affine transformation.
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- View Vertically: A Hierarchical Network for Trajectory Prediction via Fourier Spectrums104
This work proposes a hierarchical network V$^2-Net, which contains two sub-networks, to hierarchically model and predict agents' trajectories with trajectory spectrums, and shows the competitiveness and superiority of V$2$-Net on both ETH-UCY benchmark and the Stanford Drone Dataset.
- TransZero++: Cross Attribute-Guided Transformer for Zero-Shot Learning99
A cross attribute-guided Transformer network to refine visual features and learn accurate attribute localization for key semantic knowledge representations in ZSL, which achieves the new state-of-the-art results on three golden ZSL benchmarks and on the large-scale ImageNet dataset.
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Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-14. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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