23 citations · 57 across the 37 of their papers we have counts for
6 papers · 1 filter
Explainability of Deep Learning models for Urban Space perception
Ruben Sangers, Jan van Gemert, Sander van Cranenburgh
Deep learning based computer vision models are increasingly used by urban planners to support decision making for shaping urban environments. Such models predict how people perceiv…
Heart rate estimation in intense exercise videos
Yeshwanth Napolean, Anwesh Marwade, Nergis Tomen +3
Estimating heart rate from video allows non-contact health monitoring with applications in patient care, human interaction, and sports. Existing work can robustly measure heart rat…
Humans disagree with the IoU for measuring object detector localization error
Ombretta Strafforello, Vanathi Rajasekart, Osman S. Kayhan +2
The localization quality of automatic object detectors is typically evaluated by the Intersection over Union (IoU) score. In this work, we show that humans have a different view on…
Proximally Sensitive Error for Anomaly Detection and Feature Learning
Amogh Gudi, Fritjof Büttner, Jan van Gemert
Mean squared error (MSE) is one of the most widely used metrics to expression differences between multi-dimensional entities, including images. However, MSE is not locally sensitiv…
Evaluating Context for Deep Object Detectors
Osman Semih Kayhan, Jan C. van Gemert
Which object detector is suitable for your context sensitive task? Deep object detectors exploit scene context for recognition differently. In this paper, we group object detectors…
AmsterTime: A Visual Place Recognition Benchmark Dataset for Severe Domain Shift
Burak Yildiz, Seyran Khademi, Ronald Maria Siebes +1
We introduce AmsterTime: a challenging dataset to benchmark visual place recognition (VPR) in presence of a severe domain shift. AmsterTime offers a collection of 2,500 well-curate…