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This work presents CLIPDraw, an algorithm that synthesizes novel drawings based on natural language input.
Automated flower classification over a large number of classes
Nilsback, M.-E. and Zisserman, A · 2008
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Visualizing higher-layer features of a deep network
Erhan, D., Bengio, Y., Courville, A., and Vincent, P · 2009
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The caltech-ucsd birds-200-2011 dataset
Wah, C., Branson, S., Welinder, P., Perona, P., and Belongie, S · 2011
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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
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Conditional generative adversarial nets
Mirza, M. and Osindero, S · 2014
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A neural algorithm of artistic style
Gatys, L. A., Ecker, A. S., and Bethge, M · 2015
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Inceptionism: Going deeper into neural networks, 2015
Mordvintsev, A., Olah, C., and Tyka, M · 2015
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Deep neural networks are easily fooled: High confidence predictions for unrecognizable images
Nguyen, A., Yosinski, J., and Clune, J · 2015
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Synthesizing the preferred inputs for neurons in neural networks via deep generator networks
Nguyen, A., Dosovitskiy, A., Yosinski, J., Brox, T., and Clune, J · 2016
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Generative adversarial text to image synthesis
Reed, S., Akata, Z., Yan, X., Logeswaran, L., Schiele, B., and Lee, H · 2016
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Plug & play generative networks: Conditional iterative generation of images in latent space
Nguyen, A., Clune, J., Bengio, Y., Dosovitskiy, A., and Yosinski, J · 2017
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Neural discrete representation learning
Oord, A. v. d., Vinyals, O., and Kavukcuoglu, K · 2017
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Generative pretraining from pixels
Chen, M., Radford, A., Child, R., Wu, J., Jun, H., Luan, D., and Sutskever, I · 2020
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Adversarial text-to-image synthesis: A review
Frolov, S., Hinz, T., Raue, F., Hees, J., and Dengel, A · 2021
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Generating images from caption and vice versa via clip-guided generative latent space search
Galatolo, F. A., Cimino, M. G., and Vaglini, G · 2021
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The big sleep: Bigganxclip, 2021
Murdock, R · 2021
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Learning transferable visual models from natural language supervision
Radford, A., Kim, J. W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., et al · 2021
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Zero-shot text-to-image generation
Ramesh, A., Pavlov, M., Goh, G., Gray, S., Voss, C., Radford, A., Chen, M., and Sutskever, I · 2021
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Differentiable vector graphics rasterization for editing and learning
Li, T.-M., Lukáč, M., Gharbi, M., and Ragan-Kelley, J · 2020
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Generative art using neural visual grammars and dual encoders
Fernando, C., Eslami, S., Alayrac, J.-B., Mirowski, P., Banarse, D., and Osindero, S · 2021
Cited alongside, same era.
Generative adversarial networks
Goodfellow, I. J., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., and Bengio, Y
Cited in the paper.
Explaining and harnessing adversarial examples
Goodfellow, I. J., Shlens, J., and Szegedy, C
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Im2vec: Synthesizing vector graphics without vector supervision
Reddy, P., Gharbi, M., Lukac, M., and Mitra, N. J · 2021
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Clipgen: A deep generative model for clipart vectorization and synthesis
Shen, I.-C. and Chen, B.-Y · 2021
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