7 Result(s)
within
Ricardo Sanchez-Matilla
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Article
A spatio-temporal network for video semantic segmentation in surgical videos
Semantic segmentation in surgical videos has applications in intra-operative guidance, post-operative analytics and surgical education. Models need to provide accurate predictions since temporally inconsistent...
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Article
Open AccessData-centric multi-task surgical phase estimation with sparse scene segmentation
Surgical workflow estimation techniques aim to divide a surgical video into temporal segments based on predefined surgical actions or objectives, which can be of different granularity such as steps or phases. ...
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Article
Open AccessBenchmark for anonymous video analytics
Out-of-home audience measurement aims to count and characterize the people exposed to advertising content in the physical world. While audience measurement solutions based on computer vision are of increasing ...
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Chapter and Conference Paper
Scalable Joint Detection and Segmentation of Surgical Instruments with Weak Supervision
Computer vision based models, such as object segmentation, detection and tracking, have the potential to assist surgeons intra-operatively and improve the quality and outcomes of minimally invasive surgery. Di...
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Chapter and Conference Paper
Motion Prediction for First-Person Vision Multi-object Tracking
Tracking multiple independently moving objects with cameras mounted on moving robots is becoming increasingly common. However, most causal trackers rely on linear motion models that may be inaccurate in these ...
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Article
Hierarchical detection of persons in groups
In this paper, we address one of the most typical problems of person detection: scenarios with the presence of groups of persons. In this kind of scenarios, traditional person detectors have difficulties as th...
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Chapter and Conference Paper
Online Multi-target Tracking with Strong and Weak Detections
We propose an online multi-target tracker that exploits both high- and low-confidence target detections in a Probability Hypothesis Density Particle Filter framework. High-confidence (strong) detections are us...
