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Found 3 papers, 2 papers with code
Pixel-Wise Recognition for Holistic Surgical Scene Understanding
To exploit our proposed benchmark, we introduce the Transformers for Actions, Phases, Steps, and Instrument Segmentation (TAPIS) model, a general architecture that combines a global video feature extractor with localized region proposals from an instrument segmentation model to tackle the multi-granularity of our benchmark.
Ranked #2 on
Surgical phase recognition
on MISAW
A Quantitative Evaluation of Dense 3D Reconstruction of Sinus Anatomy from Monocular Endoscopic Video
In this work, we perform a quantitative analysis of a self-supervised approach for sinus reconstruction using endoscopic sequences paired with optical tracking and high-resolution computed tomography acquired from nine ex-vivo specimens.
Towards Holistic Surgical Scene Understanding
Second, we present Transformers for Action, Phase, Instrument, and steps Recognition (TAPIR) as a strong baseline for surgical scene understanding.
Ranked #3 on
Surgical phase recognition
on MISAW
