Surgical phase recognition
15 papers with code • 2 benchmarks • 2 datasets
The first 40 videos are used for training, the last 40 videos are used for testing.
Benchmarks
These leaderboards are used to track progress in Surgical phase recognition
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Cholec80
HeiChole Benchmark
Most implemented papers
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.
Metrics Matter in Surgical Phase Recognition
Surgical phase recognition is a basic component for different context-aware applications in computer- and robot-assisted surgery.
Self-Supervised Learning for Endoscopic Video Analysis
To fully exploit the power of SSL, we create sizable unlabeled endoscopic video datasets for training MSNs.
Encoding Surgical Videos as Latent Spatiotemporal Graphs for Object and Anatomy-Driven Reasoning
camma-public/surglatentgraph
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Recently, spatiotemporal graphs have emerged as a concise and elegant manner of representing video clips in an object-centric fashion, and have shown to be useful for downstream tasks such as action recognition.
