1 citations · 1 across the 6 of their papers we have counts for
5 papers · 1 filter
Beyond Few-Step Inference: Accelerating Video Diffusion Transformer Model Serving with Inter-Request Caching Reuse
Hao Liu, Ye Huang, Chenghuan Huang +5
Video Diffusion Transformer (DiT) models are a dominant approach for high-quality video generation but suffer from high inference cost due to iterative denoising. Existing caching…
SurgFed: Language-guided Multi-Task Federated Learning for Surgical Video Understanding
Zheng Fang, Ziwei Niu, Ziyue Wang +5
Surgical scene Multi-Task Federated Learning (MTFL) is essential for robot-assisted minimally invasive surgery (RAS) but remains underexplored in surgical video understanding due t…
SurGo-R1: Benchmarking and Modeling Contextual Reasoning for Operative Zone in Surgical Video
Guanyi Qin, Xiaozhen Wang, Zhu Zhuo +7
Minimally invasive surgery has dramatically improved patient operative outcomes, yet identifying safe operative zones remains challenging in critical phases, requiring surgeons to…
Structure Matters: Revisiting Boundary Refinement in Video Object Segmentation
Guanyi Qin, Ziyue Wang, Daiyun Shen +5
Given an object mask, Semi-supervised Video Object Segmentation (SVOS) technique aims to track and segment the object across video frames, serving as a fundamental task in computer…
ReSurgSAM2: Referring Segment Anything in Surgical Video via Credible Long-term Tracking
Haofeng Liu, Mingqi Gao, Xuxiao Luo +4
Surgical scene segmentation is critical in computer-assisted surgery and is vital for enhancing surgical quality and patient outcomes. Recently, referring surgical segmentation is…