Xia, Weihao;
Charette, Raoul de;
Öztireli, Cengiz;
Xue, Jing-Hao;
(2024)
DREAM: Visual Decoding from Reversing Human Visual System.
In:
2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).
(pp. pp. 8226-8235).
IEEE Xplore: Waikoloa, HI, USA.
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Abstract
In this work we present DREAM, an fMRI-to-image method for reconstructing viewed images from brain activities, grounded on fundamental knowledge of the human visual system. We craft reverse pathways that emulate the hierarchical and parallel nature of how humans perceive the visual world. These tailored pathways are specialized to decipher semantics, color, and depth cues from fMRI data, mirroring the forward pathways from visual stimuli to fMRI recordings. To do so, two components mimic the inverse processes within the human visual system: the Reverse Visual Association Cortex (R-VAC) which reverses pathways of this brain region, extracting semantics from fMRI data; the Reverse Parallel PKM (R-PKM) component simultaneously predicting color and depth from fMRI signals. The experiments indicate that our method outperforms the current state-of-the-art models in terms of the consistency of appearance, structure, and semantics. Code will be available at https://github.com/weihaox/DREAM.
Type: | Proceedings paper |
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Title: | DREAM: Visual Decoding from Reversing Human Visual System |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1109/WACV57701.2024.00804 |
Publisher version: | https://doi.org/10.1109/WACV57701.2024.00804 |
Language: | English |
Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions. |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science |
URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10184512 |
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