Online surgical phase recognition
5 papers with code • 0 benchmarks • 1 datasets
Online surgical phase recognition: the first 40 videos to train, the last 40 videos to test.
Benchmarks
These leaderboards are used to track progress in Online surgical phase recognition
Cholec80
Most implemented papers
EndoNet: A Deep Architecture for Recognition Tasks on Laparoscopic Videos
In the literature, two types of features are typically used to perform this task: visual features and tool usage signals.
Not End-to-End: Explore Multi-Stage Architecture for Online Surgical Phase Recognition
To address the problem, we propose a new non end-to-end training strategy and explore different designs of multi-stage architecture for surgical phase recognition task.
Learning from a tiny dataset of manual annotations: a teacher/student approach for surgical phase recognition
Vision algorithms capable of interpreting scenes from a real-time video stream are necessary for computer-assisted surgery systems to achieve context-aware behavior.
SKiT: a Fast Key Information Video Transformer for Online Surgical Phase Recognition
We highlight that the inference time of SKiT is constant, and independent from the input length, making it a stable choice for keeping a record of important global information, that appears on long surgical videos, essential for phase recognition.
LoViT: Long Video Transformer for Surgical Phase Recognition
MRUIL/LoViT
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Our results demonstrate the effectiveness of our approach in achieving state-of-the-art performance of surgical phase recognition on two datasets of different surgical procedures and temporal sequencing characteristics whilst introducing mechanisms that cope with long videos.
