5 papers · 1 filter
PRO-VPT: Distribution-Adaptive Visual Prompt Tuning via Prompt Relocation
Chikai Shang, Mengke Li, Yiqun Zhang +5
Visual prompt tuning (VPT), i.e., fine-tuning some lightweight prompt tokens, provides an efficient and effective approach for adapting pre-trained models to various downstream tas…
Surgical-LVLM: Learning to Adapt Large Vision-Language Model for Grounded Visual Question Answering in Robotic Surgery
Guankun Wang, Long Bai, Wan Jun Nah +7
Recent advancements in Surgical Visual Question Answering (Surgical-VQA) and related region grounding have shown great promise for robotic and medical applications, addressing the…
EndoChat: Grounded Multimodal Large Language Model for Endoscopic Surgery
Guankun Wang, Long Bai, Junyi Wang +13
Recently, Multimodal Large Language Models (MLLMs) have demonstrated their immense potential in computer-aided diagnosis and decision-making. In the context of robotic-assisted sur…
PitVis-2023 Challenge: Workflow Recognition in videos of Endoscopic Pituitary Surgery
Adrito Das, Danyal Z. Khan, Dimitrios Psychogyios +29
The field of computer vision applied to videos of minimally invasive surgery is ever-growing. Workflow recognition pertains to the automated recognition of various aspects of a sur…
Transitive Vision-Language Prompt Learning for Domain Generalization
Liyuan Wang, Yan Jin, Zhen Chen +4
The vision-language pre-training has enabled deep models to make a huge step forward in generalizing across unseen domains. The recent learning method based on the vision-language…