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Brain signal visualization has emerged as an active research area, serving as a critical interface between the human visual system and computer vision models.
WordNet: An electronic lexical database
Miller, G. A. 1998 · 1998
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Image quality assessment: from error visibility to structural similarity
Wang, Z.; Bovik, A. C.; Sheikh, H. R.; and Simoncelli, E. P. 2004 · 2004
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Individual faces elicit distinct response patterns in human anterior temporal cortex
Kriegeskorte, N.; Formisano, E.; Sorger, B.; and Goebel, R. 2007 · 2007
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Identifying natural images from human brain activity
Kay, K. N.; Naselaris, T.; Prenger, R. J.; and Gallant, J. L. 2008 · 2008
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Visual image reconstruction from human brain activity using a combination of multiscale local image decoders
Miyawaki, Y.; Uchida, H.; Yamashita, O.; Sato, M.-a.; Morito, Y.; Tanabe, H. C.; Sadato, N.; and Kamitani, Y. 2008 · 2008
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Imagenet: A large-scale hierarchical image database
Deng, J.; Dong, W.; Socher, R.; Li, L.-J.; Li, K.; and Fei-Fei, L. 2009 · 2009
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Diffwave: A versatile diffusion model for audio synthesis
Kong, Z.; Ping, W.; Huang, J.; Zhao, K.; and Catanzaro, B. 2020 · 2009
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Bayesian reconstruction of natural images from human brain activity
Naselaris, T.; Prenger, R. J.; Kay, K. N.; Oliver, M.; and Gallant, J. L. 2009 · 2009
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An image is worth 16x16 words: Transformers for image recognition at scale
Dosovitskiy, A.; Beyer, L.; Kolesnikov, A.; Weissenborn, D.; Zhai, X.; Unterthiner, T.; Dehghani, M.; Minderer, M.; Heigold, G.; Gelly, S.; et al. 2020 · 2010
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Denoising diffusion implicit models
Song, J.; Meng, C.; and Ermon, S. 2020 · 2010
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Efficient Bayesian multivariate fMRI analysis using a sparsifying spatio-temporal prior
Van Gerven, M. A.; Cseke, B.; De Lange, F. P.; and Heskes, T. 2010 · 2010
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Neural decoding with hierarchical generative models
Van Gerven, M. A.; De Lange, F. P.; and Heskes, T. 2010 · 2010
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Sun database: Large-scale scene recognition from abbey to zoo
Xiao, J.; Hays, J.; Ehinger, K. A.; Oliva, A.; and Torralba, A. 2010 · 2010
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Reconstructing visual experiences from brain activity evoked by natural movies
Nishimoto, S.; Vu, A. T.; Naselaris, T.; Benjamini, Y.; Yu, B.; and Gallant, J. L. 2011 · 2011
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Brain computer interfaces, a review
Nicolas-Alonso, L. F.; and Gomez-Gil, J. 2012 · 2012
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Decoding the representation of numerical values from brain activation patterns
Damarla, S. R.; and Just, M. A. 2013 · 2013
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Linear reconstruction of perceived images from human brain activity
Schoenmakers, S.; Barth, M.; Heskes, T.; and Van Gerven, M. 2013 · 2013
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The WU-Minn human connectome project: an overview
Van Essen, D. C.; Smith, S. M.; Barch, D. M.; Behrens, T. E.; Yacoub, E.; Ugurbil, K.; Consortium, W.-M. H.; et al. 2013 · 2013
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Microsoft coco: Common objects in context
Lin, T.-Y.; Maire, M.; Belongie, S.; Hays, J.; Perona, P.; Ramanan, D.; Dollár, P.; and Zitnick, C. L. 2014 · 2014
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Performance-optimized hierarchical models predict neural responses in higher visual cortex
Yamins, D. L.; Hong, H.; Cadieu, C. F.; Solomon, E. A.; Seibert, D.; and DiCarlo, J. J. 2014 · 2014
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Adam: A method for stochastic optimization
Kingma, D. P.; and Ba, J. 2015 · 2015
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Deep unsupervised learning using nonequilibrium thermodynamics
Sohl-Dickstein, J.; Weiss, E.; Maheswaranathan, N.; and Ganguli, S. 2015 · 2015
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Generic decoding of seen and imagined objects using hierarchical visual features
Horikawa, T.; and Kamitani, Y. 2017 · 2017
Cited alongside, same era.
Decoupled weight decay regularization
Loshchilov, I.; and Hutter, F. 2017 · 2017
RenderDiffusion: Image Diffusion for 3D Reconstruction, Inpainting and Generation
Anciukevičius, T.; Xu, Z.; Fisher, M.; Henderson, P.; Bilen, H.; Mitra, N. J.; and Guerrero, P. 2022 · 2022
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Diffusiondet: Diffusion model for object detection
Chen, S.; Sun, P.; Song, Y.; and Luo, P. 2022 · 2022
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Self-supervised natural image reconstruction and large-scale semantic classification from brain activity
Gaziv, G.; Beliy, R.; Granot, N.; Hoogi, A.; Strappini, F.; Golan, T.; and Irani, M. 2022 · 2022
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SinDDM: A Single Image Denoising Diffusion Model
Kulikov, V.; Yadin, S.; Kleiner, M.; and Michaeli, T. 2022 · 2022
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alphaXiv searches the wider corpus for related work and actual follow-ups.
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Stable long-term BCI-enabled communication in ALS and locked-in syndrome using LFP signals
Milekovic, T.; Sarma, A. A.; Bacher, D.; Simeral, J. D.; Saab, J.; Pandarinath, C.; Sorice, B. L.; Blabe, C.; Oakley, E. M.; Tringale, K. R.; et al. 2018 · 2018
Cited alongside, same era.
From voxels to pixels and back: Self-supervision in natural-image reconstruction from fMRI
Beliy, R.; Gaziv, G.; Hoogi, A.; Strappini, F.; Golan, T.; and Irani, M. 2019 · 2019
Cited alongside, same era.
BOLD5000, a public fMRI dataset while viewing 5000 visual images
Chang, N.; Pyles, J. A.; Marcus, A.; Gupta, A.; Tarr, M. J.; and Aminoff, E. M. 2019 · 2019
Cited alongside, same era.
Brain decoding of viewed image categories via semi-supervised multi-view Bayesian generative model
Akamatsu, Y.; Harakawa, R.; Ogawa, T.; and Haseyama, M. 2020 · 2020
Cited alongside, same era.
Denoising diffusion probabilistic models
Ho, J.; Jain, A.; and Abbeel, P. 2020 · 2020
Cited alongside, same era.
Label-efficient semantic segmentation with diffusion models
Baranchuk, D.; Voynov, A.; Rubachev, I.; Khrulkov, V.; and Babenko, A. 2021 · 2021
Cited alongside, same era.
Lin, C.-H.; Gao, J.; Tang, L.; Takikawa, T.; Zeng, X.; Huang, X.; Kreis, K.; Fidler, S.; Liu, M.-Y.; and Lin, T.-Y. 2022 · 2022
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Reconstruction of perceived images from fMRI patterns and semantic brain exploration using instance-conditioned GANs
Ozcelik, F.; Choksi, B.; Mozafari, M.; Reddy, L.; and VanRullen, R. 2022 · 2022
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Scalable Diffusion Models with Transformers
Peebles, W.; and Xie, S. 2022 · 2022
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Dreamfusion: Text-to-3d using 2d diffusion
Poole, B.; Jain, A.; Barron, J. T.; and Mildenhall, B. 2022 · 2022
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High-resolution image synthesis with latent diffusion models
Rombach, R.; Blattmann, A.; Lorenz, D.; Esser, P.; and Ommer, B. 2022 · 2022
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Image super-resolution via iterative refinement
Saharia, C.; Ho, J.; Chan, W.; Salimans, T.; Fleet, D. J.; and Norouzi, M. 2022 · 2022
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Tevet, G.; Raab, S.; Gordon, B.; Shafir, Y.; Cohen-Or, D.; and Bermano, A. H. 2022 · 2022
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SinDiffusion: Learning a Diffusion Model from a Single Natural Image
Wang, W.; Bao, J.; Zhou, W.; Chen, D.; Chen, D.; Yuan, L.; and Li, H. 2022 · 2022
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Tackling the Generative Learning Trilemma with Denoising Diffusion GANs
Xiao, Z.; Kreis, K.; and Vahdat, A. 2022 · 2022
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Seeing beyond the brain: Conditional diffusion model with sparse masked modeling for vision decoding
Chen, Z.; Qing, J.; Xiang, T.; Yue, W. L.; and Zhou, J. H. 2023 · 2023
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Implicit Diffusion Models for Continuous Super-Resolution
Gao, S.; Liu, X.; Zeng, B.; Xu, S.; Li, Y.; Luo, X.; Liu, J.; Zhen, X.; and Zhang, B. 2023 · 2023
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High-resolution image reconstruction with latent diffusion models from human brain activity
Takagi, Y.; and Nishimoto, S. 2023 · 2023
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Face Animation with an Attribute-Guided Diffusion Model
Zeng, B.; Liu, X.; Gao, S.; Liu, B.; Li, H.; Liu, J.; and Zhang, B. 2023 · 2023
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Adding conditional control to text-to-image diffusion models
Zhang, L.; and Agrawala, M. 2023 · 2023
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