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Understanding how the brain encodes external stimuli and how these stimuli can be decoded from the measured brain activities are long-standing and challenging questions in neuroscience.
Beyond sensory images: Object-based representation in the human ventral pathway
P. Pietrini, M. L. Furey, E. Ricciardi, M. I. Gobbini, W.-H. C. Wu, L. Cohen, M. Guazzelli, and J. V. Haxby · 2004
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Is neocortex essentially multisensory?
A. A. Ghazanfar and C. E. Schroeder · 2006
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Imagenet: A large-scale hierarchical image database
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei · 2009
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Microsoft coco: Common objects in context
T.-Y. Lin, M. Maire, S. Belongie, J. Hays, P. Perona, D. Ramanan, P. Dollár, and C. L. Zitnick · 2014
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Multisensory integration: Brain, body, and world
A. Pasqualotto, M. L. Dumitru, and A. Myachykov · 2016
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Rethinking the inception architecture for computer vision
C. Szegedy, V. Vanhoucke, S. Ioffe, J. Shlens, and Z. Wojna · 2016
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Gans trained by a two time-scale update rule converge to a local nash equilibrium
M. Heusel, H. Ramsauer, T. Unterthiner, B. Nessler, and S. Hochreiter · 2017
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Generic decoding of seen and imagined objects using hierarchical visual features
T. Horikawa and Y. Kamitani · 2017
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Neural discrete representation learning
A. Van Den Oord, O. Vinyals, et al · 2017
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BOLD5000: A public fMRI dataset of 5000 images
N. Chang, J. A. Pyles, A. Gupta, M. J. Tarr, and E. M. Aminoff · 2018
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Large-scale celebfaces attributes (celeba) dataset
Z. Liu, P. Luo, X. Wang, and X. Tang · 2018
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Conceptual captions: A cleaned, hypernymed, image alt-text dataset for automatic image captioning
P. Sharma, N. Ding, S. Goodman, and R. Soricut · 2018
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Representation learning with contrastive predictive coding
A. Van den Oord, Y. Li, and O. Vinyals · 2018
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Neural population control via deep image synthesis
P. Bashivan, K. Kar, and J. J. DiCarlo · 2019
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From voxels to pixels and back: Self-supervision in natural-image reconstruction from fmri
R. Beliy, G. Gaziv, A. Hoogi, F. Strappini, T. Golan, and M. Irani · 2019
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Causal inference in the multisensory brain
Y. Cao, C. Summerfield, H. Park, B. L. Giordano, and C. Kayser · 2019
Cited alongside, same era.
End-to-end deep image reconstruction from human brain activity
G. Shen, K. Dwivedi, K. Majima, T. Horikawa, and Y. Kamitani · 2019
Cited alongside, same era.
Deep image reconstruction from human brain activity
G. Shen, T. Horikawa, K. Majima, and Y. Kamitani · 2019
Cited alongside, same era.
Reconstructing faces from fMRI patterns using deep generative neural networks
R. VanRullen and L. Reddy · 2019
Cited alongside, same era.
Self-supervised multimodal versatile networks
J.-B. Alayrac, A. Recasens, R. Schneider, R. Arandjelović, J. Ramapuram, J. De Fauw, L. Smaira, S. Dieleman, and A. Zisserman · 2020
Perceived image decoding from brain activity using shared information of multi-subject fmri data
Y. Akamatsu, R. Harakawa, T. Ogawa, and M. Haseyama · 2021
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Vicreg: Variance-invariance-covariance regularization for self-supervised learning
A. Bardes, J. Ponce, and Y. LeCun · 2021
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Multimodal neural networks better explain multivoxel patterns in the hippocampus
B. Choksi, M. Mozafari, R. Vanrullen, and L. Reddy · 2021
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Training gans with stronger augmentations via contrastive discriminator
J. Jeong and J. Shin · 2021
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Scaling up visual and vision-language representation learning with noisy text supervision
C. Jia, Y. Yang, Y. Xia, Y.-T. Chen, Z. Parekh, H. Pham, Q. Le, Y.-H. Sung, Z. Li, and T. Duerig · 2021
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Cited alongside, same era.
Reconstructing perceptive images from brain activity by shape-semantic gan
T. Fang, Y. Qi, and G. Pan · 2020
Cited alongside, same era.
Self-supervised natural image reconstruction and rich semantic classification from brain activity
G. Gaziv, R. Beliy, N. Granot, A. Hoogi, F. Strappini, T. Golan, and M. Irani · 2020
Cited alongside, same era.
Contragan: Contrastive learning for conditional image generation
M. Kang and J. Park · 2020
Cited alongside, same era.
Training generative adversarial networks with limited data
T. Karras, M. Aittala, J. Hellsten, S. Laine, J. Lehtinen, and T. Aila · 2020
Cited alongside, same era.
Analyzing and improving the image quality of StyleGAN
T. Karras, S. Laine, M. Aittala, J. Hellsten, J. Lehtinen, and T. Aila · 2020
Cited alongside, same era.
Reconstructing natural scenes from fMRI patterns using bigbigan
M. Mozafari, L. Reddy, and R. VanRullen · 2020
Cited alongside, same era.
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Visual and linguistic semantic representations are aligned at the border of human visual cortex
S. F. Popham, A. G. Huth, N. Y. Bilenko, F. Deniz, J. S. Gao, A. O. Nunez-Elizalde, and J. L. Gallant · 2021
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Learning transferable visual models from natural language supervision
A. Radford, J. W. Kim, C. Hallacy, A. Ramesh, G. Goh, S. Agarwal, G. Sastry, A. Askell, P. Mishkin, J. Clark, et al · 2021
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Natural image reconstruction from fMRI using deep learning: A survey
Z. Rakhimberdina, Q. Jodelet, X. Liu, and T. Murata · 2021
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Zero-shot text-to-image generation
A. Ramesh, M. Pavlov, G. Goh, S. Gray, C. Voss, A. Radford, M. Chen, and I. Sutskever · 2021
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Reconstructing seen image from brain activity by visually-guided cognitive representation and adversarial learning
Z. Ren, J. Li, X. Xue, X. Li, F. Yang, Z. Jiao, and X. Gao · 2021
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Lafite: Towards language-free training for text-to-image generation
Y. Zhou, R. Zhang, C. Chen, C. Li, C. Tensmeyer, T. Yu, J. Gu, J. Xu, and T. Sun · 2021
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A massive 7T fMRI dataset to bridge cognitive neuroscience and artificial intelligence
E. J. Allen, G. St-Yves, Y. Wu, J. L. Breedlove, J. S. Prince, L. T. Dowdle, M. Nau, B. Caron, F. Pestilli, I. Charest, et al · 2022
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Hierarchical text-conditional image generation with clip latents
A. Ramesh, P. Dhariwal, A. Nichol, C. Chu, and M. Chen · 2022
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