Guoqing Xu

2 accepted papers

2026

Fine-Grained Representation for Lane Topology Reasoning

AAAI 2026technical

Precise modeling of lane topology is essential for autonomous driving, as it directly impacts navigation and control decisions. Existing methods typically represent each lane with a single query and infer topological connectivity based on the similarity between lane queries. However, this kind of de

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2026

Towards Generalizable AI-Generated Image Detection via Image-Adaptive Prompt Learning

Yiheng Li, Zichang Tan, Guoqing Xu, Zhen Lei, Xu Zhou, Yang Yang

CVPR 2026

In AI-generated image detection, current cutting-edge methods typically adapt pre-trained foundation models through partial-parameter fine-tuning. However, these approaches often struggle to generalize to forgeries from unseen generators, as the fine-tuned models capture only limited patterns from t

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