Feng Liu
Scholar

Feng Liu

Google Scholar ID: 8Y9iUz0AAAAJ
Assistant Professor, Drexel University
Computer VisionPattern RecognitionMachine LearningBiometrics
Citations & Impact
All-time
Citations
2,394
 
H-index
21
 
i10-index
25
 
Publications
20
 
Co-authors
17
list available
Resume (English only)
Academic Achievements
  • Serving as Area Chair for CVPR 2026, ICLR 2026, BMVC 2025, ACM MM 2025, FG 2025, IJCNN 2025, FG 2024, etc.
  • Recognized as ICCV 2025 Outstanding Reviewer
  • Multiple papers accepted at top-tier conferences and journals, including:
  • — ICCV 2025: HAMoBE
  • — CVPR 2025: SapiensID, AG-VPReID
  • — ECCV 2024: Open-Set Biometrics
  • — CVPR 2024: Three papers
  • — WACV 2024: FarSight
  • — ICCV 2023: Learning Clothing and Pose Invariant 3D Shape Representation for Long-Term Person Re-Identification
  • — CVPR 2023: DCFace
  • — IEEE TPAMI: Learning Implicit Functions for Dense 3D Shape Correspondence of Generic Objects
  • — NeurIPS 2022: Cluster and Aggregate: Face Recognition with Large Probe Set
  • — ECCV 2022: 2D GANs Meet Unsupervised Single-View 3D Reconstruction, Controllable and Guided Face Synthesis for Unconstrained Face Recognition
  • — NeurIPS 2021: Voxel-based 3D Detection and Reconstruction of Multiple Objects from a Single Image
  • — IJCV: Shape My Face: Registering 3D Face Scans by Surface-to-Surface Translation
  • — CVPR 2021: Fully Understanding Generic Objects: Modeling, Segmentation, and Reconstruction
  • — NeurIPS 2020 (Oral presentation, 1.1% acceptance rate): Learning Implicit Functions for Topology-Varying Dense 3D Shape Correspondence
Background
  • Assistant Professor in the Department of Computer Science at Drexel University
  • Research interests include: 3D Computer Vision (3D object/scene understanding, 3D generation, VR/AR, 3D vision+language understanding)
  • AI + X (Education, Healthcare)
  • 3D Human Digitization (Modeling, reconstruction and rendering, Biomechanics)
  • Generative AI (Explainability, generalization and controllability in generative models, DeepFake detection)
  • Biometric Recognition (Face and gait recognition, Person re-identification)