25 citations · 70 across the 6 of their papers we have counts for
6 papers
Why is the winner the best?
Matthias Eisenmann, Annika Reinke, Vivienn Weru +122
International benchmarking competitions have become fundamental for the comparative performance assessment of image analysis methods. However, little attention has been given to in…
Self-distillation for surgical action recognition
Amine Yamlahi, Thuy Nuong Tran, Patrick Godau +9
Surgical scene understanding is a key prerequisite for contextaware decision support in the operating room. While deep learning-based approaches have already reached or even surpas…
Weakly Supervised Temporal Convolutional Networks for Fine-grained Surgical Activity Recognition
Sanat Ramesh, Diego Dall'Alba, Cristians Gonzalez +6
Automatic recognition of fine-grained surgical activities, called steps, is a challenging but crucial task for intelligent intra-operative computer assistance. The development of c…
Temporally Constrained Neural Networks (TCNN): A framework for semi-supervised video semantic segmentation
Deepak Alapatt, Pietro Mascagni, Armine Vardazaryan +7
A major obstacle to building models for effective semantic segmentation, and particularly video semantic segmentation, is a lack of large and well annotated datasets. This bottlene…
Single- and Multi-Task Architectures for Surgical Workflow Challenge at M2CAI 2016
Andru P. Twinanda, Didier Mutter, Jacques Marescaux +2
The surgical workflow challenge at M2CAI 2016 consists of identifying 8 surgical phases in cholecystectomy procedures. Here, we propose to use deep architectures that are based on…
Single- and Multi-Task Architectures for Tool Presence Detection Challenge at M2CAI 2016
Andru P. Twinanda, Didier Mutter, Jacques Marescaux +2
The tool presence detection challenge at M2CAI 2016 consists of identifying the presence/absence of seven surgical tools in the images of cholecystectomy videos. Here, we propose t…