Search Results for author: Idoia Ruiz

Found 4 papers, 1 papers with code

Weakly Supervised Multi-Object Tracking and Segmentation

no code implementations3 Jan 2021 Idoia Ruiz, Lorenzo Porzi, Samuel Rota Bulò, Peter Kontschieder, Joan Serrat

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 not provide any kind of mask annotation.

Instance Segmentation Multi-Object Tracking +4

Learning Multi-Object Tracking and Segmentation from Automatic Annotations

no code implementations CVPR 2020 Lorenzo Porzi, Markus Hofinger, Idoia Ruiz, Joan Serrat, Samuel Rota Bulò, Peter Kontschieder

Training MOTSNet with our automatically extracted data leads to significantly improved sMOTSA scores on the novel KITTI MOTS dataset (+1. 9%/+7. 5% on cars/pedestrians), and MOTSNet improves by +4. 1% over previously best methods on the MOTSChallenge dataset.

Association Instance Segmentation +4

Optimizing speed/accuracy trade-off for person re-identification via knowledge distillation

no code implementations7 Dec 2018 Idoia Ruiz, Bogdan Raducanu, Rakesh Mehta, Jaume Amores

Additionally, we propose and analyse network distillation as a learning strategy to reduce the computational cost of the deep learning approach at test time.

General Classification Knowledge Distillation +2

Metric Learning for Novelty and Anomaly Detection

1 code implementation16 Aug 2018 Marc Masana, Idoia Ruiz, Joan Serrat, Joost Van de Weijer, Antonio M. Lopez

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 too confidently.

Anomaly Detection Metric Learning +2

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