collaborators

7 papers

eess.IV2026

PriSAR: 3D Geometric-Prior-Guided Diffusion for Parameter-Controlled SAR Image Generation

Fan Zhang, Xuanting Wu, Fei Ma +2

Synthetic aperture radar (SAR) image generation can mitigate data scarcity, but controllablegeneration under sparse observation angles remains difficult. Recent SAR generative stud…

eess.IV2026

Cross-Sensor SAR Data Generation Using Diffusion Models and Feature Migration

Xuanting Wu, Fan Zhang, Fei Ma +2

Different synthetic aperture radar (SAR) sensors vary significantly in resolution, polarization modes, and frequency bands, making it difficult to directly apply existing models to…

eess.IV2026

A Task-Driven and Quality-Assured Agent Framework for SAR Data Generation

Xuanting Wu, Fan Zhanga, Fei Ma +3

Synthetic aperture radar (SAR) data augmentation is important for improving the generalization of data-driven SAR interpretation models, yet practical augmentation workflows are of…

cs.CV2026

Optical-Guided Neural Collapse for SAR Few-Shot Class Incremental Learning

Fan Zhang, Sijin Zheng, Fei Ma +4

Few-shot class-incremental learning (FSCIL) in synthetic aperture radar imagery presents unique challenges due to severe data scarcity and SAR-specific variability. In particular,…

eess.IV2026

GeoDiff-SAR II: 3D-Driven Foundation Diffusion Models for SAR Generation via Decoupled Control

Xuanting Wu, Fan Zhang, Fei Ma +4

Existing Synthetic Aperture Radar (SAR) image generation methods still lack reliable controllability over key imaging parameters, particularly azimuth angle, depression angle, and…

eess.IV2026

GeoDiff-SAR: A Geometric Prior Guided Diffusion Model for SAR Image Generation

Fan Zhang, Xuanting Wu, Fei Ma +2

Synthetic aperture radar (SAR) image generation can mitigate data scarcity, but controllablegeneration under sparse observation angles remains difficult. Recent SAR generative stud…