Tianfu Wu

Biography

Tianfu Wu is an associate professor in the Department of Electrical and Computer Engineering at NC State University. He is currently the PI of the laboratory of interpretable Visual Modeling, Computing and Learning (iVMCL).  He received his Ph.D. in statistics from UCLA under the supervision by Prof. Song-Chun Zhu. His research focuses on interpretable Visual Modeling, Computing and Learning, often motivated by the tasks of pursuing a unified framework for AI to ALTER (Ask, Learn, Test, Explain and Refine) in a trustworthy, robust and responsive way for AIGCGT (AI Generated Content and Ground-Truth).

Education

• Ph.D. 2011
  Statistics
  University of California, Los Angeles

Recent Publications

• Sign-Based Gradient Descent With Heterogeneous Data: Convergence and Byzantine Resilience (2024)
• CGBA: Curvature-aware Geometric Black-box Attack (2023)
• CGBA: Curvature-aware Geometric Black-box Attack (2023)
• Holistically-Attracted Wireframe Parsing: From Supervised to Self-Supervised Learning (2023)
• LEARNING SPATIALLY-ADAPTIVE SQUEEZE-EXCITATION NETWORKS FOR FEW SHOT IMAGE SYNTHESIS (2023)
• LEARNING SPATIALLY-ADAPTIVE STYLE-MODULATION NETWORKS FOR SINGLE IMAGE SYNTHESIS (2023)
• Level-S²fM: Structure from Motion on Neural Level Set of Implicit Surfaces (2023)
• Monocular 3D Object Detection with Bounding Box Denoising in 3D by Perceiver (2023)
• NOPE-SAC: Neural One-Plane RANSAC for Sparse-View Planar 3D Reconstruction (2023)
• PaCa-ViT: Learning Patch-to-Cluster Attention in Vision Transformers (2023)