World's Best Scientists 2026 revealed!
Tyng-Luh Liu

Tyng-Luh Liu

D-Index & Metrics

Computer Science

D-Index
32
Citations
5198
World Ranking
13056
National Ranking
120

Best Publications

  • Local discriminant embedding and its variants

    Unknown

  • Fusing generic objectness and visual saliency for salient object detection

    Kai-Yueh Chang;Tyng-Luh Liu;Hwann-Tzong Chen;Shang-Hong Lai

  • Multiple Kernel Learning for Dimensionality Reduction

    Yen-Yu Lin;Tyng-Luh Liu;Chiou-Shann Fuh

  • From co-saliency to co-segmentation: An efficient and fully unsupervised energy minimization model

    Kai-Yueh Chang;Tyng-Luh Liu;Shang-Hong Lai

  • Cube Padding for Weakly-Supervised Saliency Prediction in 360° Videos

    Hsien-Tzu Cheng;Chun-Hung Chao;Jin-Dong Dong;Hao-Kai Wen

  • Approximate tree matching and shape similarity

    Unknown

  • Real-time tracking using trust-region methods

    Unknown

  • Representation and self-similarity of shapes

    D. Geiger;Tyng-Luh Liu;R.V. Kohn

  • Regularized Background Adaptation: A Novel Learning Rate Control Scheme for Gaussian Mixture Modeling

    Unknown

  • Semantic manifold learning for image retrieval

    Yen-Yu Lin;Tyng-Luh Liu;Hwann-Tzong Chen

  • Capturing Humans in Motion: Temporal-Attentive 3D Human Pose and Shape Estimation from Monocular Video

    Unknown

  • Decoupled Contrastive Learning

    Chun-Hsiao Yeh;Cheng-Yao Hong;Yen-Chi Hsu;Tyng-Luh Liu

  • See-Through-Text Grouping for Referring Image Segmentation

    Unknown

  • One-Shot Object Detection with Co-Attention and Co-Excitation

    Unknown

  • Multi-object tracking using dynamical graph matching

    Unknown

  • Local Ensemble Kernel Learning for Object Category Recognition

    Yen-Yu Lin;Tyng-Luh Liu;Chiou-Shann Fuh

  • Text-Guided Graph Neural Networks for Referring 3D Instance Segmentation.

    Unknown

  • Learning a Scene Background Model via Classification

    Unknown

  • Self-supervised Sparse Representation for Video Anomaly Detection

    Unknown

  • A probabilistic SVM approach for background scene initialization

    Unknown

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