We present a new egocentric procedural error dataset containing videos with various types
of errors as well as normal videos and propose a new framework for procedural error …

We study supervised action segmentation whose goal is to predict framewise action labels
of a video. To capture temporal dependencies over long horizons prior works either improve …

We address the problem of online action segmentation for egocentric procedural task
videos. While previous studies have mostly focused on offline action segmentation where …

Automatic surgical workflow analysis, which aims to recognize the ongoing surgical events
in videos, is fundamental for develo** context-aware computer-assisted systems. This …

Surgical practice involves complex visual interpretation, procedural skills, and advanced
medical knowledge, making surgical vision-language pretraining (VLP) particularly …

Existing state-of-the-art methods for surgical phase recognition either rely on the extraction
of spatial-temporal features at a short-range temporal resolution or adopt the sequential …

Artificial intelligence (AI) has emerged as a transformative tool in surgery, particularly in
telesurgery and telementoring. However, its potential to enhance data transmission …

Pringle maneuver (PM) in laparoscopic liver resection aims to reduce blood loss and
provide a clear surgical view by intermittently blocking blood inflow of the liver, whereas …

Objective: To enable context-aware computer assistance in the operating room of the future,
cognitive systems need to understand automatically which surgical phase is being …

Purpose: Surgical phase recognition (SPR) is an integral component of surgical data
science, enabling high-level surgical analysis. End-to-end trained neural networks that …