5 papers
UHR-Net: An Uncertainty-Aware Hypergraph Refinement Network for Medical Image Segmentation
Shuokun Cheng, Jinghao Shi, Kun Sun
Accurate lesion segmentation is crucial for clinical diagnosis and treatment planning. However, lesions often resemble surrounding tissues and exhibit ill-defined boundaries, leadi…
RACANet: Reliability-Aware Crowd Anchor Network for RGB-T Crowd Counting
Jinghao Shi, Mengqi Lei, Kunliang He +3
RGB-Thermal (T) crowd counting aims to integrate visible-spectrum and thermal infrared information to improve the robustness of crowd density estimation in complex scenes. Although…
BiCoR-Seg: Bidirectional Co-Refinement Framework for High-Resolution Remote Sensing Image Segmentation
Jinghao Shi, Jianing Song
High-resolution remote sensing image semantic segmentation (HRSS) is a fundamental yet critical task in the field of Earth observation. However, it has long faced the challenges of…
Embedding-based Retrieval in Multimodal Content Moderation
Hanzhong Liang, Jinghao Shi, Xiang Shen +6
Video understanding plays a fundamental role for content moderation on short video platforms, enabling the detection of inappropriate content. While classification remains the domi…
CPFD: Confidence-aware Privileged Feature Distillation for Short Video Classification
Jinghao Shi, Xiang Shen, Kaili Zhao +5
Dense features, customized for different business scenarios, are essential in short video classification. However, their complexity, specific adaptation requirements, and high comp…