Showing cs.CVShow all
3 papers · 1 filter
cs.CV2024
MS-TCRNet: Multi-Stage Temporal Convolutional Recurrent Networks for Action Segmentation Using Sensor-Augmented Kinematics
Adam Goldbraikh, Omer Shubi, Or Rubin +2
Action segmentation is a challenging task in high-level process analysis, typically performed on video or kinematic data obtained from various sensors. This work presents two contr…
cs.CV2024
Robust Surgical Phase Recognition From Annotation Efficient Supervision
Or Rubin, Shlomi Laufer
Surgical phase recognition is a key task in computer-assisted surgery, aiming to automatically identify and categorize the different phases within a surgical procedure. Despite sub…
cs.CV2024
CuVLER: Enhanced Unsupervised Object Discoveries through Exhaustive Self-Supervised Transformers
Shahaf Arica, Or Rubin, Sapir Gershov +1
In this paper, we introduce VoteCut, an innovative method for unsupervised object discovery that leverages feature representations from multiple self-supervised models. VoteCut emp…