publications

journals

2023

2023

  1. JoV
    Color and gloss constancy under diverse lighting environments
    Takuma Morimoto, Arash Akbarinia, Katherine Storrs, Jacob R. Cheeseman, and 3 more authors
    Journal of Vision, Jul 2023
  2. csf.png
    Contrast sensitivity function in deep networks
    Arash Akbarinia, Yaniv Morgenstern, and Karl R. Gegenfurtner
    Neural Networks, Jul 2023
  3. Pat. Rec.
    Dense Extreme Inception Network for Edge Detection
    Xavier Soria, Angel Sappa, Patricio Humanante, and Arash Akbarinia
    Pattern Recognition, Jul 2023

2022

2022

  1. eLife
    Emergent color categorization in a neural network trained for object recognition
    Jelmer P Vries, Arash Akbarinia, Alban Flachot, and Karl R Gegenfurtner
    eLife, Jul 2022
  2. JoV
    Deep neural models for color classification and color constancy
    Alban Flachot, Arash Akbarinia, Heiko H Schütt, Roland W Fleming, and 2 more authors
    Journal of Vision, Jul 2022

2021

2021

  1. colour_conversion.png
    Color Conversion in deep autoencoders
    Arash Akbarinia, and Raquel Gil-Rodrı́guez
    Journal of Perceptual Imaging, Jul 2021
  2. Sci. Rep.
    Deep neural network model of haptic saliency
    Anna Metzger, Matteo Toscani, Arash Akbarinia, Matteo Valsecchi, and 1 more author
    Scientific Reports, Jul 2021

2020

2020

  1. decipher_contrast.png
    Deciphering image contrast in object classification deep networks
    Arash Akbarinia, and Raquel Gil-Rodrı́guez
    Vision Research, Jul 2020

2018

2018

  1. IJCV
    Feedback and surround modulated boundary detection
    Arash Akbarinia, and C Alejandro Parraga
    International Journal of Computer Vision, Jul 2018
  2. JOSA A
    Color metamerism and the structure of illuminant space
    Arash Akbarinia, and Karl R Gegenfurtner
    JOSA A, Jul 2018

2017

2017

  1. pami_dog_thumbnail.png
    Colour constancy beyond the classical receptive field
    Arash Akbarinia, and C Alejandro Parraga
    IEEE Transactions on Pattern Analysis and Machine Intelligence, Jul 2017

2016

2016

  1. PLOS One
    NICE: A computational solution to close the gap from colour perception to colour categorization
    C Alejandro Parraga, and Arash Akbarinia
    PloS one, Jul 2016

book chapters

2020

2020

  1. Enc. Color
    Color Name Applications in Computer Vision
    C. Alejandro Parraga, and Arash Akbarinia
    Encyclopedia of Color Science and Technology, 2020

peer-reviewed conferences

2020

2020

  1. ETRA
    Pedestrians Egocentric Vision: Individual and Collective Analysis
    Matteo Valsecchi, Arash Akbarinia, Raquel Gil-Rodriguez, and Karl R Gegenfurtner
    In ACM Symposium on Eye Tracking Research and Applications, 2020

2017

2017

  1. IPTA
    Multispectral single-sensor RGB-NIR imaging: New challenges and opportunities
    Xavier Soria, Angel D Sappa, and Arash Akbarinia
    In 2017 Seventh International Conference on Image Processing Theory, Tools and Applications (IPTA), 2017
  2. BMVC
    Colour Constancy: Biologically-inspired Contrast Variant Pooling Mechanism
    Arash Akbarinia, Raquel Gil-Rodríguez, and C Alejandro Parraga
    In Proceedings of the British Machine Vision Conference (BMVC), Sep 2017

2016

2016

  1. BMVC
    Biologically plausible boundary detection
    Arash Akbarinia, and Alejandro Parraga
    In Proceedings of the British Machine Vision Conference (BMVC), Sep 2016

2015

2015

  1. APCASE
    Real-Time Face Detection and Tracking Utilising OpenMP and ROS
    Eduardo Tusa, Arash Akbarinia, Raquel Gil Rodriguez, and Corina Barbalata
    In Asia-Pacific Conference on Computer Aided System Engineering, Sep 2015

preprints

2024

2024

  1. bioRxiv
    Exploring the Categorical Nature of Colour Perception: Insights from Artificial Networks
    Arash Akbarinia
    bioRxiv, 2024

2020

2020

  1. arXiv
    The Utility of Decorrelating Colour Spaces in Vector Quantised Variational Autoencoders
    Arash Akbarinia, Raquel Gil-Rodrı́guez, Alban Flachot, and Matteo Toscani
    arXiv preprint arXiv:2009.14487, 2020

2019

2019

  1. arXiv
    Paradox in deep neural networks: Similar yet different while different yet similar
    Arash Akbarinia, and Karl R Gegenfurtner
    arXiv preprint arXiv:1903.04772, 2019