CAMMA-public/rendezvous
A transformer-inspired neural network for surgical action triplet recognition from laparoscopic videos.
This project helps surgical teams and researchers automatically analyze laparoscopic videos by identifying specific actions occurring during an operation. It takes raw surgical video footage as input and outputs detailed descriptions of surgical activities, such as "grasper, grasping, gallbladder." This tool is ideal for surgical educators, researchers studying surgical efficiency, or anyone involved in developing automated surgical assistants.
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Use this if you need to precisely identify specific instruments, actions, and targets within endoscopic surgical videos for training, research, or quality improvement.
Not ideal if you need to analyze non-surgical video content or require real-time, in-situ surgical guidance rather than post-operative video analysis.
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Python
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Last pushed
Sep 17, 2025
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