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Yongxiang Liu

4 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author2
  • last author2

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV2
  • eess.IV2
same name
  • Yongxiang Liu — 9 papers
  • Yongxiang Liu — 2 papers, h 4
  • Yongxiang Liu — 2 papers
  • Yongxiang Liu — 1 paper
  • Yongxiang Liu — 1 paper
  • Yongxiang Liu — 1 paper

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

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

7 citations · 7 across the 4 of their papers we have counts for

collaborators

4 papers

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…

eess.IV2025

SAR-GTR: Attributed Scattering Information Guided SAR Graph Transformer Recognition Algorithm

Xuying Xiong, Xinyu Zhang, Weidong Jiang +3

Utilizing electromagnetic scattering information for SAR data interpretation is currently a prominent research focus in the SAR interpretation domain. Graph Neural Networks (GNNs)…

eess.IV2024

MaDiNet: Mamba Diffusion Network for SAR Target Detection

Jie Zhou, Chao Xiao, Bowen Peng +4

The fundamental challenge in SAR target detection lies in developing discriminative, efficient, and robust representations of target characteristics within intricate non-cooperativ…

cs.CV2024

UEVAVD: A Dataset for Developing UAV's Eye View Active Object Detection

Xinhua Jiang, Tianpeng Liu, Li Liu +2

Occlusion is a longstanding difficulty that challenges the UAV-based object detection. Many works address this problem by adapting the detection model. However, few of them exploit…

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