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surgfutr
Publiccholectrack20
PublicCVS-AdaptNet
PublicEndoshare_code
PublicEndoshare
PublicUltraSam
Publiccamma_dataset_overlaps
PublicMultiBypass140
PublicTF-Cholec80
Publiccholect45
PublicLaparoscopic video dataset for surgical action triplet recognitionattention-tripnet
Publictripnet
Publicrendezvous-in-time
Publiccholect50
PublicA repository for surgical action triplet dataset. Data are videos of laparoscopic cholecystectomy that have been annotated with <instrument, verb, target> labels for every surgical fine-grained activity.rendezvous
PublicA transformer-inspired neural network for surgical action triplet recognition from laparoscopic videos.cholectriplet2022
PublicSurgLatentGraph
PublicThis repository contains the code associated with our 2023 TMI paper "Latent Graph Representations for Critical View of Safety Assessment" and our MICCAI 2023 paper "Encoding Surgical Videos as Spatiotemporal Graphs for Object and Anatomy-Driven Reasoning".Endoscapes
PublicMML-SurgAdapt
PublicSurgVLP
PublicPeskaVLP
PublicSelf-MVA
PublicOfficial code for "Learning from Synchronization: Self-Supervised Uncalibrated Multi-View Person Association in Challenging Scenes"surgitrack
Publiccholescore
PublicTFUScapes
PublicORPose-Depth
PublicInference demo and evaluation scripts for the MICCAI-2019 paper "Human Pose Estimation on Privacy-Preserving Low-Resolution Depth Images"MVOR
PublicMulti-View Operating Room (MVOR) dataset consists of synchronized multi-view frames recorded by three RGB-D cameras in a hybrid OR during real clinical interventions. We provide camera calibration parameters, color and depth frames, human bounding boxes, and 2D/3D pose annotations. The MVOR was released in the MICCAI-LABELS 2018 workshop.ORPose-Color
PublicInference demo for the MICCAI-2020 paper "Self-supervision on Unlabelled OR Data for Multi-person 2D/3D Human Pose Estimation"AI4surgery
PublicShort tutorial supplementing the Neural Networks and Deep Learning chapter from Artificial Intelligence in Surgery: An AI Primer for Surgical Practice designed to offer hands-on experience with artificial neural networks to surgeons with little to no coding experience.HPE-AdaptOR
Public