Pau Rodríguez

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Element AI Inc ∙ Universitat Autònoma de Barcelona

Hierarchical Residual Attention Network for Single Image Super-Resolution

Convolutional neural networks are the most successful models in single i...
12/08/2020 ∙ by Parichehr Behjati, et al. ∙ 4 ∙ share

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Counting Cows: Tracking Illegal Cattle Ranching From High-Resolution Satellite Imagery

Cattle farming is responsible for 8.8% of greenhouse gas emissions world...
11/14/2020 ∙ by Issam Laradji, et al. ∙ 4 ∙ share

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Affinity LCFCN: Learning to Segment Fish with Weak Supervision

Aquaculture industries rely on the availability of accurate fish body me...
11/06/2020 ∙ by Issam Laradji, et al. ∙ 16 ∙ share

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Synbols: Probing Learning Algorithms with Synthetic Datasets

Progress in the field of machine learning has been fueled by the introdu...
09/14/2020 ∙ by Alexandre Lacoste, et al. ∙ 58 ∙ share

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CVPR 2020 Continual Learning in Computer Vision Competition: Approaches, Results, Current Challenges and Future Directions

In the last few years, we have witnessed a renewed and fast-growing inte...
09/14/2020 ∙ by Vincenzo Lomonaco, et al. ∙ 75 ∙ share

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OverNet: Lightweight Multi-Scale Super-Resolution with Overscaling Network

Super-resolution (SR) has achieved great success due to the development ...
08/05/2020 ∙ by Parichehr Behjati, et al. ∙ 0 ∙ share

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A Weakly Supervised Consistency-based Learning Method for COVID-19 Segmentation in CT Images

Acquiring count annotations generally requires less human effort than po...
07/04/2020 ∙ by Issam Laradji, et al. ∙ 16 ∙ share

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LOOC: Localize Overlapping Objects with Count Supervision

Acquiring count annotations generally requires less human effort than po...
07/03/2020 ∙ by Issam H. Laradji, et al. ∙ 3 ∙ share

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Online Fast Adaptation and Knowledge Accumulation: a New Approach to Continual Learning

Learning from non-stationary data remains a great challenge for machine ...
03/12/2020 ∙ by Massimo Caccia, et al. ∙ 26 ∙ share

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Embedding Propagation: Smoother Manifold for Few-Shot Classification

Few-shot classification is challenging because the data distribution of ...
03/09/2020 ∙ by Pau Rodríguez, et al. ∙ 4 ∙ share

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Attend and Rectify: a Gated Attention Mechanism for Fine-Grained Recovery

We propose a novel attention mechanism to enhance Convolutional Neural N...
07/19/2018 ∙ by Pau Rodríguez, et al. ∙ 2 ∙ share

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Beyond One-hot Encoding: lower dimensional target embedding

Target encoding plays a central role when learning Convolutional Neural ...
06/28/2018 ∙ by Pau Rodríguez, et al. ∙ 0 ∙ share

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TADAM: Task dependent adaptive metric for improved few-shot learning

Few-shot learning has become essential for producing models that general...
05/23/2018 ∙ by Boris N. Oreshkin, et al. ∙ 0 ∙ share

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Deep Inference of Personality Traits by Integrating Image and Word Use in Social Networks

Social media, as a major platform for communication and information exch...
02/06/2018 ∙ by Guillem Cucurull, et al. ∙ 0 ∙ share

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Regularizing CNNs with Locally Constrained Decorrelations

Regularization is key for deep learning since it allows training more co...
11/07/2016 ∙ by Pau Rodríguez, et al. ∙ 0 ∙ share

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Pau Rodríguez

Featured Co-authors

Yu Chen

Sergio Escalera

David Vazquez

Laurent Charlin

Irina Rish

Alexandre Lacoste

Min Lin

German I. Parisi

Vincenzo Lomonaco

Issam Laradji

Derek Nowrouzezahrai

Hierarchical Residual Attention Network for Single Image Super-Resolution

Counting Cows: Tracking Illegal Cattle Ranching From High-Resolution Satellite Imagery

Affinity LCFCN: Learning to Segment Fish with Weak Supervision

Synbols: Probing Learning Algorithms with Synthetic Datasets

CVPR 2020 Continual Learning in Computer Vision Competition: Approaches, Results, Current Challenges and Future Directions

OverNet: Lightweight Multi-Scale Super-Resolution with Overscaling Network

A Weakly Supervised Consistency-based Learning Method for COVID-19 Segmentation in CT Images

LOOC: Localize Overlapping Objects with Count Supervision

Online Fast Adaptation and Knowledge Accumulation: a New Approach to Continual Learning

Embedding Propagation: Smoother Manifold for Few-Shot Classification

Attend and Rectify: a Gated Attention Mechanism for Fine-Grained Recovery

Beyond One-hot Encoding: lower dimensional target embedding

TADAM: Task dependent adaptive metric for improved few-shot learning

Deep Inference of Personality Traits by Integrating Image and Word Use in Social Networks

Regularizing CNNs with Locally Constrained Decorrelations