activity
20242026
most citedTimeline and Boundary Guided Diffusion Network for Video Shadow Detection

15 citations · 22 across the 14 of their papers we have counts for

collaborators

17 papers

eess.IV2026

SegRap2025: A Benchmark of Gross Tumor Volume and Lymph Node Clinical Target Volume Segmentation for Radiotherapy Planning of Nasopharyngeal Carcinoma

Jia Fu, Litingyu Wang, He Li +27

Accurate delineation of Gross Tumor Volume (GTV), Lymph Node Clinical Target Volume (LN CTV), and Organ-at-Risk (OAR) from Computed Tomography (CT) scans is essential for precise r…

cs.CV2026

Toward Real-World High-Precision Image Matting and Segmentation

Haipeng Zhou, Zhaohu Xing, Hongqiu Wang +3

High-precision scene parsing tasks, including image matting and dichotomous segmentation, aim to accurately predict masks with extremely fine details (such as hair). Most existing…

cs.CV2026

VQ-Seg: Vector-Quantized Token Perturbation for Semi-Supervised Medical Image Segmentation

Sicheng Yang, Zhaohu Xing, Lei Zhu

Consistency learning with feature perturbation is a widely used strategy in semi-supervised medical image segmentation. However, many existing perturbation methods rely on dropout,…

cs.CV2025

K-Stain: Keypoint-Driven Correspondence for H&E-to-IHC Virtual Staining

Sicheng Yang, Zhaohu Xing, Haipeng Zhou +1

Virtual staining offers a promising method for converting Hematoxylin and Eosin (H&E) images into Immunohistochemical (IHC) images, eliminating the need for costly chemical process…

cs.CV2025

Surgical-MambaLLM: Mamba2-enhanced Multimodal Large Language Model for VQLA in Robotic Surgery

Pengfei Hao, Hongqiu Wang, Shuaibo Li +4

In recent years, Visual Question Localized-Answering in robotic surgery (Surgical-VQLA) has gained significant attention for its potential to assist medical students and junior doc…

cs.CV2025

Toward Medical Deepfake Detection: A Comprehensive Dataset and Novel Method

Shuaibo Li, Zhaohu Xing, Hongqiu Wang +4

The rapid advancement of generative AI in medical imaging has introduced both significant opportunities and serious challenges, especially the risk that fake medical images could u…