Xavier Boix

According to our database, Xavier Boix authored at least 55 papers between 2009 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Transformer Module Networks for Systematic Generalization in Visual Question Answering.

Moyuru Yamada, Vanessa D'Amario, Kentaro Takemoto, Xavier Boix, Tomotake Sasaki

IEEE Trans. Pattern Anal. Mach. Intell., December, 2024

D3: Data Diversity Design for Systematic Generalization in Visual Question Answering.

Amir Rahimi, Vanessa D'Amario, Moyuru Yamada, Kentaro Takemoto, Tomotake Sasaki, Xavier Boix

Trans. Mach. Learn. Res., 2024

Task Arithmetic Through The Lens Of One-Shot Federated Learning.

Zhixu Tao, Ian Mason, Sanjeev R. Kulkarni, Xavier Boix

CoRR, 2024

Rethinking VLMs and LLMs for Image Classification.

Avi Cooper, Keizo Kato, Chia-Hsien Shih, Hiroaki Yamane, Kasper Vinken, Kentaro Takemoto, Taro Sunagawa, Hao-Wei Yeh, Jin Yamanaka, Ian Mason, Xavier Boix

CoRR, 2024

Configural processing as an optimized strategy for robust object recognition in neural networks.

Hojin Jang, Pawan Sinha, Xavier Boix

CoRR, 2024

2023

Robustness to Transformations Across Categories: Is Robustness Driven by Invariant Neural Representations?

Hojin Jang, Syed Suleman Abbas Zaidi, Xavier Boix, Neeraj Prasad, Sharon Gilad-Gutnick, Shlomit Ben-Ami, Pawan Sinha

Neural Comput., December, 2023

Multi-domain improves out-of-distribution and data-limited scenarios for medical image analysis.

Ece Ozkan, Xavier Boix

CoRR, 2023

Modularity Trumps Invariance for Compositional Robustness.

Ian Mason, Anirban Sarkar, Tomotake Sasaki, Xavier Boix

CoRR, 2023

Deephys: Deep Electrophysiology, Debugging Neural Networks under Distribution Shifts.

Anirban Sarkar, Matthew Groth, Ian Mason, Tomotake Sasaki, Xavier Boix

CoRR, 2023

2022

Three approaches to facilitate invariant neurons and generalization to out-of-distribution orientations and illuminations.

Akira Sakai, Taro Sunagawa, Spandan Madan, Kanata Suzuki, Takashi Katoh, Hiromichi Kobashi, Hanspeter Pfister, Pawan Sinha, Xavier Boix, Tomotake Sasaki

Neural Networks, 2022

When and how convolutional neural networks generalize to out-of-distribution category-viewpoint combinations.

Spandan Madan, Timothy Henry, Jamell Dozier, Helen Ho, Nishchal Bhandari, Tomotake Sasaki, Frédo Durand, Hanspeter Pfister, Xavier Boix

Nat. Mach. Intell., 2022

The Data Efficiency of Deep Learning Is Degraded by Unnecessary Input Dimensions.

Vanessa D'Amario, Sanjana Srivastava, Tomotake Sasaki, Xavier Boix

Frontiers Comput. Neurosci., 2022

2021

Do Neural Networks for Segmentation Understand Insideness?

Kimberly Villalobos, Vilim Stih, Amineh Ahmadinejad, Shobhita Sundaram, Jamell Dozier, Andrew Francl, Frederico Azevedo, Tomotake Sasaki, Xavier Boix

Neural Comput., 2021

A Robust Optimization Approach to Deep Learning.

Dimitris Bertsimas, Xavier Boix, Kimberly Villalobos Carballo, Dick den Hertog

CoRR, 2021

Symmetry Perception by Deep Networks: Inadequacy of Feed-Forward Architectures and Improvements with Recurrent Connections.

Shobhita Sundaram, Darius Sinha, Matthew Groth, Tomotake Sasaki, Xavier Boix

CoRR, 2021

Three approaches to facilitate DNN generalization to objects in out-of-distribution orientations and illuminations: late-stopping, tuning batch normalization and invariance loss.

Akira Sakai, Taro Sunagawa, Spandan Madan, Kanata Suzuki, Takashi Katoh, Hiromichi Kobashi, Hanspeter Pfister, Pawan Sinha, Xavier Boix, Tomotake Sasaki

CoRR, 2021

To Which Out-Of-Distribution Object Orientations Are DNNs Capable of Generalizing?

Avi Cooper, Xavier Boix, Daniel Harari, Spandan Madan, Hanspeter Pfister, Tomotake Sasaki, Pawan Sinha

CoRR, 2021

The Foes of Neural Network's Data Efficiency Among Unnecessary Input Dimensions.

Vanessa D'Amario, Sanjana Srivastava, Tomotake Sasaki, Xavier Boix

CoRR, 2021

Small in-distribution changes in 3D perspective and lighting fool both CNNs and Transformers.

Spandan Madan, Tomotake Sasaki, Tzu-Mao Li, Xavier Boix, Hanspeter Pfister

CoRR, 2021

How Modular should Neural Module Networks Be for Systematic Generalization?

Vanessa D'Amario, Tomotake Sasaki, Xavier Boix

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Frivolous Units: Wider Networks Are Not Really That Wide.

Stephen Casper, Xavier Boix, Vanessa D'Amario, Ling Guo, Martin Schrimpf, Kasper Vinken, Gabriel Kreiman

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

On the Capability of Neural Networks to Generalize to Unseen Category-Pose Combinations.

Spandan Madan, Timothy Henry, Jamell Dozier, Helen Ho, Nishchal Bhandari, Tomotake Sasaki, Frédo Durand, Hanspeter Pfister, Xavier Boix

CoRR, 2020

Is Robustness To Transformations Driven by Invariant Neural Representations?

Syed Suleman Abbas Zaidi, Xavier Boix, Neeraj Prasad, Sharon Gilad-Gutnick, Shlomit Ben-Ami, Pawan Sinha

CoRR, 2020

2019

Removable and/or Repeated Units Emerge in Overparametrized Deep Neural Networks.

Stephen Casper, Xavier Boix, Vanessa D'Amario, Ling Guo, Martin Schrimpf, Kasper Vinken, Gabriel Kreiman

CoRR, 2019

Minimal Images in Deep Neural Networks: Fragile Object Recognition in Natural Images.

Sanjana Srivastava, Guy Ben-Yosef, Xavier Boix

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Theory IIIb: Generalization in Deep Networks.

Tomaso A. Poggio, Qianli Liao, Brando Miranda, Andrzej Banburski, Xavier Boix, Jack Hidary

CoRR, 2018

Theory of Deep Learning III: explaining the non-overfitting puzzle.

Tomaso A. Poggio, Kenji Kawaguchi, Qianli Liao, Brando Miranda, Lorenzo Rosasco, Xavier Boix, Jack Hidary, Hrushikesh N. Mhaskar

CoRR, 2018

2017

Reports on the 2017 AAAI Spring Symposium Series.

Jeannette Bohg, Xavier Boix, Nancy Chang, Elizabeth F. Churchill, Vivian Chu, Fei Fang, Jerome Feldman, Avelino J. Gonzalez, Takashi Kido, William F. Lawless, José L. Montaña, Santiago Ontañón, Jivko Sinapov, Donald A. Sofge, Luc Steels, Molly Wright Steenson, Keiki Takadama, Amulya Yadav

AI Mag., 2017

Predicting When Eye Fixations Are Consistent.

Anna Volokitin, Michael Gygli, Xavier Boix

Proceedings of the 2017 AAAI Spring Symposia, 2017

Eccentricity Dependent Deep Neural Networks: Modeling Invariance in Human Vision.

Francis X. Chen, Gemma Roig, Leyla Isik, Xavier Boix, Tomaso A. Poggio

Proceedings of the 2017 AAAI Spring Symposia, 2017

Active Video Summarization: Customized Summaries via On-line Interaction with the User.

Ana Garcia del Molino, Xavier Boix, Joo-Hwee Lim, Ah-Hwee Tan

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

Learning to Predict Sequences of Human Visual Fixations.

Ming Jiang, Xavier Boix, Gemma Roig, Juan Xu, Luc Van Gool, Qi Zhao

IEEE Trans. Neural Networks Learn. Syst., 2016

Herding Generalizes Diverse M -Best Solutions.

Ece Ozkan, Gemma Roig, Orcun Goksel, Xavier Boix

CoRR, 2016

Predicting When Saliency Maps are Accurate and Eye Fixations Consistent.

Anna Volokitin, Michael Gygli, Xavier Boix

Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

2015

Computational commonalities of image understanding algorithms.

Xavier Boix

PhD thesis, 2015

SEEDS: Superpixels Extracted Via Energy-Driven Sampling.

Michael Van den Bergh, Xavier Boix, Gemma Roig, Luc Van Gool

Int. J. Comput. Vis., 2015

Foveation-based Mechanisms Alleviate Adversarial Examples.

Yan Luo, Xavier Boix, Gemma Roig, Tomaso A. Poggio, Qi Zhao

CoRR, 2015

SALICON: Reducing the Semantic Gap in Saliency Prediction by Adapting Deep Neural Networks.

Xun Huang, Chengyao Shen, Xavier Boix, Qi Zhao

Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

Saliency Prediction with Active Semantic Segmentation.

Ming Jiang, Xavier Boix, Juan Xu, Gemma Roig, Luc Van Gool, Qi Zhao

Proceedings of the British Machine Vision Conference 2015, 2015

2014

Comment on "Ensemble Projection for Semi-supervised Image Classification".

Xavier Boix, Gemma Roig, Luc Van Gool

CoRR, 2014

Self-Adaptable Templates for Feature Coding.

Xavier Boix, Gemma Roig, Salomon Diether, Luc Van Gool

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Reconstruction of Inextensible Surfaces on a Budget via Bootstrapping.

Alex Locher, Lennart Elsen, Xavier Boix, Luc Van Gool

Proceedings of the 2nd International Conference on 3D Vision, 2014

2013

Random Binary Mappings for Kernel Learning and Efficient SVM.

Gemma Roig, Xavier Boix, Luc Van Gool

CoRR, 2013

Active MAP Inference in CRFs for Efficient Semantic Segmentation.

Gemma Roig, Xavier Boix, Roderick de Nijs, Sebastian Ramos, Kolja Kühnlenz, Luc Van Gool

Proceedings of the IEEE International Conference on Computer Vision, 2013

Online Video SEEDS for Temporal Window Objectness.

Michael Van den Bergh, Gemma Roig, Xavier Boix, Santiago Manen, Luc Van Gool

Proceedings of the IEEE International Conference on Computer Vision, 2013

Sparse Quantization for Patch Description.

Xavier Boix, Michael Gygli, Gemma Roig, Luc Van Gool

Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013

2012

Harmony Potentials - Fusing Global and Local Scale for Semantic Image Segmentation.

Xavier Boix, Josep M. Gonfaus, Joost van de Weijer, Andrew D. Bagdanov, Joan Serrat Gual, Jordi Gonzàlez

Int. J. Comput. Vis., 2012

On-line semantic perception using uncertainty.

Roderick de Nijs, Sebastian Ramos, Gemma Roig, Xavier Boix, Luc Van Gool, Kolja Kühnlenz

Proceedings of the 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2012

Nested Sparse Quantization for Efficient Feature Coding.

Xavier Boix, Gemma Roig, Christian Leistner, Luc Van Gool

Proceedings of the Computer Vision - ECCV 2012, 2012

SEEDS: Superpixels Extracted via Energy-Driven Sampling.

Michael Van den Bergh, Xavier Boix, Gemma Roig, Benjamin de Capitani, Luc Van Gool

Proceedings of the Computer Vision - ECCV 2012, 2012

2011

Conditional Random Fields for multi-camera object detection.

Gemma Roig, Xavier Boix, Horesh Ben Shitrit, Pascal Fua

Proceedings of the IEEE International Conference on Computer Vision, 2011

Are spatial and global constraints really necessary for segmentation?

Aurélien Lucchi, Yunpeng Li, Xavier Boix Bosch, Kevin Smith, Pascal Fua

Proceedings of the IEEE International Conference on Computer Vision, 2011

Hierarchical CRF with product label spaces for parts-based models.

Gemma Roig, Xavier Boix Bosch, Fernando De la Torre, Joan Serrat Gual, Carles Vilella

Proceedings of the Ninth IEEE International Conference on Automatic Face and Gesture Recognition (FG 2011), 2011

2010

Harmony potentials for joint classification and segmentation.

Josep M. Gonfaus, Xavier Boix Bosch, Joost van de Weijer, Andrew D. Bagdanov, Joan Serrat Gual, Jordi Gonzàlez

Proceedings of the Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition, 2010

2009

Optimal feature selection for subspace image matching.

Gemma Roig, Xavier Boix, Fernando De la Torre

Proceedings of the 12th IEEE International Conference on Computer Vision Workshops, 2009