5 papers
Delta Sampling R-BERT for limited data and low-light action recognition
Sanchit Hira, Ritwik Das, Abhinav Modi +1
We present an approach to perform supervised action recognition in the dark. In this work, we present our results on the ARID dataset. Most previous works only evaluate performance…
Towards Unsupervised Learning for Instrument Segmentation in Robotic Surgery with Cycle-Consistent Adversarial Networks
Daniil Pakhomov, Wei Shen, Nassir Navab
Surgical tool segmentation in endoscopic images is an important problem: it is a crucial step towards full instrument pose estimation and it is used for integration of pre- and int…
Searching for Efficient Architecture for Instrument Segmentation in Robotic Surgery
Daniil Pakhomov, Nassir Navab
Segmentation of surgical instruments is an important problem in robot-assisted surgery: it is a crucial step towards full instrument pose estimation and is directly used for maskin…
Comparative evaluation of instrument segmentation and tracking methods in minimally invasive surgery
Sebastian Bodenstedt, Max Allan, Anthony Agustinos +17
Intraoperative segmentation and tracking of minimally invasive instruments is a prerequisite for computer- and robotic-assisted surgery. Since additional hardware like tracking sys…
Deep Residual Learning for Instrument Segmentation in Robotic Surgery
Daniil Pakhomov, Vittal Premachandran, Max Allan +2
Detection, tracking, and pose estimation of surgical instruments are crucial tasks for computer assistance during minimally invasive robotic surgery. In the majority of cases, the…