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20232026
most citedDiffDet4SAR: Diffusion-based Aircraft Target Detection Network for SAR Images

74 citations · 174 across the 9 of their papers we have counts for

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6 papers · 1 filter

cs.CV2026

MMATR-X: High-Resolution Optical-SAR Joint Pretraining via Conditioned Alignment and Degraded-Target Prediction

Bowen Peng, Yongxiang Liu, Jie Zhou +4

Joint optical and Synthetic Aperture Radar (SAR) pretraining seeks cross-modal gains over representations learned from either modality alone. This is challenging because the modali…

cs.CV2026

HuiYanEarth-SAR: A Foundation Model for High-Fidelity and Low-Cost Global Remote Sensing Imagery Generation

Yongxiang Liu, Jie Zhou, Yafei Song +2

Synthetic Aperture Radar (SAR) imagery generation is essential for deepening the study of scattering mechanisms, establishing trustworthy electromagnetic scene models, and fundamen…

cs.CV2025★ 7 cited

A Reverse Causal Framework to Mitigate Spurious Correlations for Debiasing Scene Graph Generation

Shuzhou Sun, Li Liu, Tianpeng Liu +4

Existing two-stage Scene Graph Generation (SGG) frameworks typically incorporate a detector to extract relationship features and a classifier to categorize these relationships; the…

cs.CV2024

Step-wise Distribution Alignment Guided Style Prompt Tuning for Source-free Cross-domain Few-shot Learning

Huali Xu, Li Liu, Tianpeng Liu +3

Existing cross-domain few-shot learning (CDFSL) methods, which develop source-domain training strategies to enhance model transferability, face challenges with large-scale pre-trai…

cs.CV2023★ 71 cited

Predicting Gradient is Better: Exploring Self-Supervised Learning for SAR ATR with a Joint-Embedding Predictive Architecture

Weijie Li, Yang Wei, Tianpeng Liu +5

The growing Synthetic Aperture Radar (SAR) data has the potential to build a foundation model through Self-Supervised Learning (SSL) methods, which can achieve various SAR Automati…

cs.CV2023

Fast Sparse PCA via Positive Semidefinite Projection for Unsupervised Feature Selection

Junjing Zheng, Xinyu Zhang, Yongxiang Liu +3

In the field of unsupervised feature selection, sparse principal component analysis (SPCA) methods have attracted more and more attention recently. Compared to spectral-based metho…