6 papers
SA-Person: Text-Based Person Retrieval with Scene-aware Re-ranking
Yingjia Xu, Jinlin Wu, Daming Gao +5
Text-based person retrieval aims to identify a target individual from an image gallery using a natural language description. Existing methods primarily focus on appearance-driven c…
SurgLLM: A Versatile Large Multimodal Model with Spatial Focus and Temporal Awareness for Surgical Video Understanding
Zhen Chen, Xingjian Luo, Kun Yuan +6
Surgical video understanding is crucial for facilitating Computer-Assisted Surgery (CAS) systems. Despite significant progress in existing studies, two major limitations persist, i…
Learning to Efficiently Adapt Foundation Models for Self-Supervised Endoscopic 3D Scene Reconstruction from Any Cameras
Beilei Cui, Long Bai, Mobarakol Islam +8
Accurate 3D scene reconstruction is essential for numerous medical tasks. Given the challenges in obtaining ground truth data, there has been an increasing focus on self-supervised…
SurgPLAN++: Universal Surgical Phase Localization Network for Online and Offline Inference
Zhen Chen, Xingjian Luo, Jinlin Wu +5
Surgical phase recognition is critical for assisting surgeons in understanding surgical videos. Existing studies focused more on online surgical phase recognition, by leveraging pr…
Advancing Dense Endoscopic Reconstruction with Gaussian Splatting-driven Surface Normal-aware Tracking and Mapping
Yiming Huang, Beilei Cui, Long Bai +5
Simultaneous Localization and Mapping (SLAM) is essential for precise surgical interventions and robotic tasks in minimally invasive procedures. While recent advancements in 3D Gau…
EndoOmni: Zero-Shot Cross-Dataset Depth Estimation in Endoscopy by Robust Self-Learning from Noisy Labels
Qingyao Tian, Zhen Chen, Huai Liao +4
Single-image depth estimation is essential for endoscopy tasks such as localization, reconstruction, and augmented reality. Most existing methods in surgical scenes focus on in-dom…