Search Results for author: Xavier Giró-i-Nieto

Found 21 papers, 15 papers with code

HyperFast: Instant Classification for Tabular Data

1 code implementation22 Feb 2024 David Bonet, Daniel Mas Montserrat, Xavier Giró-i-Nieto, Alexander G. Ioannidis

Training deep learning models and performing hyperparameter tuning can be computationally demanding and time-consuming.

AutoML Classification

Sign Language Translation from Instructional Videos

1 code implementation13 Apr 2023 Laia Tarrés, Gerard I. Gállego, Amanda Duarte, Jordi Torres, Xavier Giró-i-Nieto

We report a result of 8. 03 on the BLEU score, and publish the first open-source implementation of its kind to promote further advances.

Sign Language Translation

Tackling Low-Resourced Sign Language Translation: UPC at WMT-SLT 22

1 code implementation2 Dec 2022 Laia Tarrés, Gerard I. Gàllego, Xavier Giró-i-Nieto, Jordi Torres

This paper describes the system developed at the Universitat Polit\`ecnica de Catalunya for the Workshop on Machine Translation 2022 Sign Language Translation Task, in particular, for the sign-to-text direction.

Data Augmentation FocusNews (test) +4

Hyper-Representations as Generative Models: Sampling Unseen Neural Network Weights

1 code implementation29 Sep 2022 Konstantin Schürholt, Boris Knyazev, Xavier Giró-i-Nieto, Damian Borth

Learning representations of neural network weights given a model zoo is an emerging and challenging area with many potential applications from model inspection, to neural architecture search or knowledge distillation.

Knowledge Distillation Neural Architecture Search +1

Model Zoos: A Dataset of Diverse Populations of Neural Network Models

1 code implementation29 Sep 2022 Konstantin Schürholt, Diyar Taskiran, Boris Knyazev, Xavier Giró-i-Nieto, Damian Borth

With this work, we publish a novel dataset of model zoos containing systematically generated and diverse populations of NN models for further research.

Classification Friction

Hyper-Representations for Pre-Training and Transfer Learning

1 code implementation22 Jul 2022 Konstantin Schürholt, Boris Knyazev, Xavier Giró-i-Nieto, Damian Borth

Learning representations of neural network weights given a model zoo is an emerging and challenging area with many potential applications from model inspection, to neural architecture search or knowledge distillation.

Knowledge Distillation Neural Architecture Search +4

Sign Language Video Retrieval with Free-Form Textual Queries

no code implementations CVPR 2022 Amanda Duarte, Samuel Albanie, Xavier Giró-i-Nieto, Gül Varol

Systems that can efficiently search collections of sign language videos have been highlighted as a useful application of sign language technology.

Retrieval Sentence +2

Multiple Object Tracking with Mixture Density Networks for Trajectory Estimation

no code implementations21 Jun 2021 Andreu Girbau, Xavier Giró-i-Nieto, Ignasi Rius, Ferran Marqués

In this work, we show that trajectory estimation can become a key factor for tracking, and present TrajE, a trajectory estimator based on recurrent mixture density networks, as a generic module that can be added to existing object trackers.

Ranked #23 on Multi-Object Tracking on MOT17 (MOTA metric)

Multi-Object Tracking Multiple Object Tracking +1

Curriculum Learning for Recurrent Video Object Segmentation

1 code implementation15 Aug 2020 Maria Gonzalez-i-Calabuig, Carles Ventura, Xavier Giró-i-Nieto

Video object segmentation can be understood as a sequence-to-sequence task that can benefit from the curriculum learning strategies for better and faster training of deep neural networks.

Object Semantic Segmentation +2

Assessing Knee OA Severity with CNN attention-based end-to-end architectures

1 code implementation23 Aug 2019 Marc Górriz, Joseph Antony, Kevin McGuinness, Xavier Giró-i-Nieto, Noel E. O'Connor

This work proposes a novel end-to-end convolutional neural network (CNN) architecture to automatically quantify the severity of knee osteoarthritis (OA) using X-Ray images, which incorporates trainable attention modules acting as unsupervised fine-grained detectors of the region of interest (ROI).

Test

Hyperparameter-Free Losses for Model-Based Monocular Reconstruction

1 code implementation16 Aug 2019 Eduard Ramon, Guillermo Ruiz, Thomas Batard, Xavier Giró-i-Nieto

This work proposes novel hyperparameter-free losses for single view 3D reconstruction with morphable models (3DMM).

3D Reconstruction Benchmarking +2

The Liver Tumor Segmentation Benchmark (LiTS)

6 code implementations13 Jan 2019 Patrick Bilic, Patrick Christ, Hongwei Bran Li, Eugene Vorontsov, Avi Ben-Cohen, Georgios Kaissis, Adi Szeskin, Colin Jacobs, Gabriel Efrain Humpire Mamani, Gabriel Chartrand, Fabian Lohöfer, Julian Walter Holch, Wieland Sommer, Felix Hofmann, Alexandre Hostettler, Naama Lev-Cohain, Michal Drozdzal, Michal Marianne Amitai, Refael Vivantik, Jacob Sosna, Ivan Ezhov, Anjany Sekuboyina, Fernando Navarro, Florian Kofler, Johannes C. Paetzold, Suprosanna Shit, Xiaobin Hu, Jana Lipková, Markus Rempfler, Marie Piraud, Jan Kirschke, Benedikt Wiestler, Zhiheng Zhang, Christian Hülsemeyer, Marcel Beetz, Florian Ettlinger, Michela Antonelli, Woong Bae, Míriam Bellver, Lei Bi, Hao Chen, Grzegorz Chlebus, Erik B. Dam, Qi Dou, Chi-Wing Fu, Bogdan Georgescu, Xavier Giró-i-Nieto, Felix Gruen, Xu Han, Pheng-Ann Heng, Jürgen Hesser, Jan Hendrik Moltz, Christian Igel, Fabian Isensee, Paul Jäger, Fucang Jia, Krishna Chaitanya Kaluva, Mahendra Khened, Ildoo Kim, Jae-Hun Kim, Sungwoong Kim, Simon Kohl, Tomasz Konopczynski, Avinash Kori, Ganapathy Krishnamurthi, Fan Li, Hongchao Li, Junbo Li, Xiaomeng Li, John Lowengrub, Jun Ma, Klaus Maier-Hein, Kevis-Kokitsi Maninis, Hans Meine, Dorit Merhof, Akshay Pai, Mathias Perslev, Jens Petersen, Jordi Pont-Tuset, Jin Qi, Xiaojuan Qi, Oliver Rippel, Karsten Roth, Ignacio Sarasua, Andrea Schenk, Zengming Shen, Jordi Torres, Christian Wachinger, Chunliang Wang, Leon Weninger, Jianrong Wu, Daguang Xu, Xiaoping Yang, Simon Chun-Ho Yu, Yading Yuan, Miao Yu, Liping Zhang, Jorge Cardoso, Spyridon Bakas, Rickmer Braren, Volker Heinemann, Christopher Pal, An Tang, Samuel Kadoury, Luc Soler, Bram van Ginneken, Hayit Greenspan, Leo Joskowicz, Bjoern Menze

In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LiTS), which was organized in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI) 2017 and the International Conferences on Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2017 and 2018.

Benchmarking Computed Tomography (CT) +3

Cross-modal Embeddings for Video and Audio Retrieval

1 code implementation7 Jan 2018 Didac Surís, Amanda Duarte, Amaia Salvador, Jordi Torres, Xavier Giró-i-Nieto

The increasing amount of online videos brings several opportunities for training self-supervised neural networks.

Retrieval

Semantic Summarization of Egocentric Photo Stream Events

1 code implementation2 Nov 2015 Aniol Lidon, Marc Bolaños, Mariella Dimiccoli, Petia Radeva, Maite Garolera, Xavier Giró-i-Nieto

With the rapid increase of users of wearable cameras in recent years and of the amount of data they produce, there is a strong need for automatic retrieval and summarization techniques.

Image Retrieval Retrieval

End-to-end Convolutional Network for Saliency Prediction

1 code implementation6 Jul 2015 Junting Pan, Xavier Giró-i-Nieto

The prediction of saliency areas in images has been traditionally addressed with hand crafted features based on neuroscience principles.

Saliency Prediction

Improving Spatial Codification in Semantic Segmentation

no code implementations27 May 2015 Carles Ventura, Xavier Giró-i-Nieto, Verónica Vilaplana, Kevin McGuinness, Ferran Marqués, Noel E. O'Connor

This paper explores novel approaches for improving the spatial codification for the pooling of local descriptors to solve the semantic segmentation problem.

Object Segmentation +2

Visual Summary of Egocentric Photostreams by Representative Keyframes

1 code implementation5 May 2015 Marc Bolaños, Ricard Mestre, Estefanía Talavera, Xavier Giró-i-Nieto, Petia Radeva

Building a visual summary from an egocentric photostream captured by a lifelogging wearable camera is of high interest for different applications (e. g. memory reinforcement).

Clustering Test

Exploring EEG for Object Detection and Retrieval

no code implementations9 Apr 2015 Eva Mohedano, Amaia Salvador, Sergi Porta, Xavier Giró-i-Nieto, Graham Healy, Kevin McGuinness, Noel O'Connor, Alan F. Smeaton

We show that it is indeed possible to detect such objects in complex images and, also, that users with previous knowledge on the dataset or experience with the RSVP outperform others.

Content-Based Image Retrieval EEG +5

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