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Xiaotian Qiao

10 accepted papers

2026

LayoutAD: Exploring Semantic-Geometric Misalignment Reasoning for Scene Layout Anomaly Detection

CVPR 2026

Visual anomaly detection is vital for quality control applications by identifying deviations from normal patterns. Previous structural or logical anomaly detection methods mainly focus on pixel-level deviations like texture defects and reconstruction errors, ignoring the object-level structural and

Cited by 0SourceScholar
2026

RSA-CR: Resisting Shilling Attacks in Citation Recommendation via Dumbbell Inductive Learning

AAAI 2026technical

Citation recommendation aims to provide researchers with the most relevant references for their manuscripts, helping them swiftly discover pertinent studies and bolster the reliability of their arguments. However, some individuals manipulate these recommendation systems by injecting false informatio

Cited by 0SourcePDFScholar
2025

CollageNoter: Real-Time and Adaptive Collage Layout Design for Screenshot-Based E-Note-Taking

AAAI 2025technical

To enhance the processing of complex multi-modal documents (e.g. e-books, long web pages, etc.), it is an efficient way for users to take digital screenshots of key parts and reorganize them into a new collage E-Note. Existing methods for assisting collage layout design primarily employ a semantic…

Cited by 0SourcePDFScholar
2025

HDLayout: Hierarchical and Directional Layout Planning for Arbitrary Shaped Visual Text Generation

AAAI 2025technical

Visual text generation, which aims to generate photo-realistic images with coherent and well-formed scene text being rendered, has attracted widespread attention. Although recent works have achieved promising performance, the limited flexibility and controllability hinder their practical application…

Cited by 0SourcePDFScholar
2025

Less is More: Efficient Image Vectorization with Adaptive Parameterization

CVPR 2025poster

Image vectorization aims to convert raster images to vector ones, allowing for easy scaling and editing.Existing works mainly rely on preset parameters (i.e., a fixed number of paths and control points), ignoring the complexity of the image and posing significant challenges to practical applications…

Cited by 0SourcePDFScholar
2025

Under the Shadow: Exploiting Opacity Variation for Fine-grained Shadow Detection

NeurIPS 2025poster

Shadow characteristics are of great importance for scene understanding. Existing works mainly consider shadow regions as binary masks, often leading to imprecise detection results and suboptimal performance for scene understanding. We demonstrate that such an assumption oversimplifies light-…

Cited by 0SourceScholar