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cs.CV2021
Weakly Supervised Multi-Object Tracking and Segmentation
Idoia Ruiz, Lorenzo Porzi, Samuel Rota Bulò +2
We introduce the problem of weakly supervised Multi-Object Tracking and Segmentation, i.e. joint weakly supervised instance segmentation and multi-object tracking, in which we do n…
cs.CV2019
Learning Multi-Object Tracking and Segmentation from Automatic Annotations
Lorenzo Porzi, Markus Hofinger, Idoia Ruiz +3
In this work we contribute a novel pipeline to automatically generate training data, and to improve over state-of-the-art multi-object tracking and segmentation (MOTS) methods. Our…
cs.CV2018
Metric Learning for Novelty and Anomaly Detection
Marc Masana, Idoia Ruiz, Joan Serrat +2
When neural networks process images which do not resemble the distribution seen during training, so called out-of-distribution images, they often make wrong predictions, and do so…