Scholar
Zhixuan Li
Google Scholar ID: SoWWEB8AAAAJ
Research Fellow, CCDS, Nanyang Technological University (Singapore)
Citations & Impact
Citations
264
H-index
7
i10-index
7
Publications
16
Co-authors
7
list available
Publications
Resume (English only)
Academic Achievements
- - Publications:
- - Shape Distribution Matters: Shape-specific Mixture-of-Experts for Amodal Segmentation under Diverse Occlusions (arXiv, 2025)
- - Single Point, Full Mask: Velocity-Guided Level Set Evolution for End-to-End Amodal Segmentation (arXiv, 2025)
- - BEAT: Balanced Frequency Adaptive Tuning for Long-Term Time-Series Forecasting (arXiv, 2025)
- - Unveiling the Invisible: Reasoning Complex Occlusions Amodally with AURA (ICCV, 2025)
- - BLADE: Box-Level Supervised Amodal Segmentation through Directed Expansion (AAAI, 2024)
- - GIN: Generative INvariant Shape Prior for Amodal Instance Segmentation (TMM, 2023)
- - MUVA: A New Large-Scale Benchmark for Multi-view Amodal Instance Segmentation in the Shopping Scenario (ICCV, 2023)
- - OAFormer: Learning Occlusion Distinguishable Feature for Amodal Instance Segmentation (ICASSP, 2023)
- - 2D Amodal Instance Segmentation Guided by 3D Shape Prior (ECCV, 2022)
- - LVPNet: A Latent-variable-based Prediction-driven End-to-end Framework for Lossless Compression of Medical Images (MICCAI, 2025)
- - MS-IQA: A Multi-Scale Feature Fusion Network for PET/CT Image Quality Assessment (MICCAI, 2025)
- - VIPNet: Combining Viewpoint Information and Shape Priors for Instant Multi-View 3D Reconstruction (ACCV, 2024)
Research Experience
- - Research Fellow: College of Computing and Data Science (CCDS), Nanyang Technological University, collaborating with Prof. Weisi Lin
Education
- - Ph.D. degree: National Engineering Research Center of Visual Technology (NERCVT), Peking University, 2023, supervised by Prof. Tiejun Huang and Assoc. Prof. Tingting Jiang
- - B.E. degree: Tianjin University, 2018, supervised by Prof. Pengfei Zhu and Prof. Di Jin
Background
- Research interests include Artificial Intelligence, Computer Vision, and Deep Learning, especially in the fields of complex occlusion scene understanding, amodal segmentation, visual reasoning, climate change forecasting, and time-series analysis.
Miscellany
- Projects: Awesome Mixture-of-Experts list (GitHub link)
