From the 7 of 76 papers with an AI index.
63 citations
- Peking UniversityCN37 papers
- Hunan UniversityCN35 papers
- Tsinghua UniversityCN34 papers
- University of Science and Technology of ChinaCN34 papers
- Guangxi Normal UniversityCN33 papers
- Lanzhou UniversityCN33 papers
- Zhejiang UniversityCN33 papers
- Beihang UniversityCN32 papers
- Nanjing Normal UniversityCN32 papers
- Nanjing UniversityCN32 papers
- Ruhr University BochumDE32 papers
- Shanghai Jiao Tong UniversityCN32 papers
12 papers · 1 filter
3D Modeling and Automated Measurement of Concrete Cracks via Segment Anything Refinement and Visual Inertial LiDAR Fusion
Pengru Deng, Jiapeng Yao, Chun Li +4
Visual-Spatial Systems has become increasingly essential in concrete crack inspection. However, existing methods often lacks adaptability to diverse scenarios, exhibits limited rob…
A cross-modal network for facial expression recognition
Chunwei Tian, Jingyuan Xie, Qi Zhang +3
Deep neural networks enriched with structural information have been widely employed for facial expression recognition tasks. However, these methods often depend on hierarchical inf…
TextGround4M: A Prompt-Aligned Dataset for Layout-Aware Text Rendering
Dongxing Mao, Yilin Wang, Linjie Li +2
Despite recent advances in text-to-image generation, models still struggle to accurately render prompt-specified text with correct spatial layout -- especially in multi-span, struc…
Exploring Boundary-Aware Spatial-Frequency Fusion for Camouflaged Object Detection
Song Yu, Yang Hu, Haokang Ding +2
Camouflaged Object Detection is challenging due to the high degree of similarity between camouflaged objects and their surrounding backgrounds. Current COD methods mainly rely on e…
FGML-DG: Feynman-Inspired Cognitive Science Paradigm for Cross-Domain Medical Image Segmentation
Yucheng Song, Chenxi Li, Haokang Ding +2
In medical image segmentation across multiple modalities (e.g., MRI, CT, etc.) and heterogeneous data sources (e.g., different hospitals and devices), Domain Generalization (DG) re…
Tracking by Detection and Query: An Efficient End-to-End Framework for Multi-Object Tracking
Shukun Jia, Shiyu Hu, Yichao Cao +3
Multi-object tracking (MOT) is primarily dominated by two paradigms: tracking-by-detection (TBD) and tracking-by-query (TBQ). While TBD offers modular efficiency, its fragmented as…