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20172019
most citedSimultaneous Recognition and Pose Estimation of Instruments in Minimally Invasive Surgery

88 citations · 88 across the 3 of their papers we have counts for

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8 papers · 1 filter

cs.CV2019

Recover and Identify: A Generative Dual Model for Cross-Resolution Person Re-Identification

Yu-Jhe Li, Yun-Chun Chen, Yen-Yu Lin +2

Person re-identification (re-ID) aims at matching images of the same identity across camera views. Due to varying distances between cameras and persons of interest, resolution mism…

cs.CV2019

Learning Resolution-Invariant Deep Representations for Person Re-Identification

Yun-Chun Chen, Yu-Jhe Li, Xiaofei Du +1

Person re-identification (re-ID) solves the task of matching images across cameras and is among the research topics in vision community. Since query images in real-world scenarios…

cs.CV2018

Toward Scale-Invariance and Position-Sensitive Region Proposal Networks

Hsueh-Fu Lu, Xiaofei Du, Ping-Lin Chang

Accurately localising object proposals is an important precondition for high detection rate for the state-of-the-art object detection frameworks. The accuracy of an object detectio…

cs.CV2018

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…

cs.CV2018

Adaptation and Re-Identification Network: An Unsupervised Deep Transfer Learning Approach to Person Re-Identification

Yu-Jhe Li, Fu-En Yang, Yen-Cheng Liu +3

Person re-identification (Re-ID) aims at recognizing the same person from images taken across different cameras. To address this task, one typically requires a large amount labeled…

cs.CV201788 cited

Simultaneous Recognition and Pose Estimation of Instruments in Minimally Invasive Surgery

Thomas Kurmann, Pablo Marquez Neila, Xiaofei Du +4

Detection of surgical instruments plays a key role in ensuring patient safety in minimally invasive surgery. In this paper, we present a novel method for 2D vision-based recognitio…