Fetching the paper…
Reading the bibliography…
Recent advances in text-to-image generative models provide the ability to generate high-quality images from short text descriptions.
Multiscale structural similarity for image quality assessment
Wang, Z., Simoncelli, E., and Bovik, A · 2003
Earlier work this paper cites.
Holistically-nested edge detection
Xie, S. and Tu, Z · 2015
Earlier work this paper cites.
Variable rate image compression with recurrent neural networks
Toderici, G., O’Malley, S. M., Hwang, S. J., Vincent, D., Minnen, D., Baluja, S., Covell, M., and Sukthankar, R · 2016
Earlier work this paper cites.
Ntire 2017 challenge on single image super-resolution: Dataset and study
Agustsson, E. and Timofte, R · 2017
Earlier work this paper cites.
Soft-to-hard vector quantization for end-to-end learning compressible representations
Agustsson, E., Mentzer, F., Tschannen, M., Cavigelli, L., Timofte, R., Benini, L., and Gool, L. V · 2017
Earlier work this paper cites.
End-to-end optimized image compression
Ballé, J., Laparra, V., and Simoncelli, E. P · 2017
Earlier work this paper cites.
Gans trained by a two time-scale update rule converge to a local nash equilibrium
Heusel, M., Ramsauer, H., Unterthiner, T., Nessler, B., and Hochreiter, S · 2017
Earlier work this paper cites.
Lossy image compression with compressive autoencoders
Theis, L., Shi, W., Cunningham, A., and Huszár, F · 2017
Earlier work this paper cites.
Towards improved lossy image compression: Human image reconstruction with public-domain images
Bhown, A., Mukherjee, S., Yang, S., Chandak, S., Fischer-Hwang, I., Tatwawadi, K., Fan, J., and Weissman, T · 2018
Earlier work this paper cites.
Bińkowski, M., Sutherland, D. J., Arbel, M., and Gretton, A · 2018
Earlier work this paper cites.
The unreasonable effectiveness of deep features as a perceptual metric
Zhang, R., Isola, P., Efros, A. A., Shechtman, E., and Wang, O · 2018
Earlier work this paper cites.
Generative adversarial networks for extreme learned image compression
Agustsson, E., Tschannen, M., Mentzer, F., Timofte, R., and Gool, L. V · 2019
Earlier work this paper cites.
Humans are still the best lossy image compressors
Bhown, A., Mukherjee, S., Yang, S., Chandak, S., Fischer-Hwang, I., Tatwawadi, K., and Weissman, T · 2019
Earlier work this paper cites.
Rethinking lossy compression: The rate-distortion-perception tradeoff
Blau, Y. and Michaeli, T · 2019
Cited alongside, same era.
Video enhancement with task-oriented flow
Xue, T., Chen, B., Wu, J., Wei, D., and Freeman, W. T · 2019
Cited alongside, same era.
Nonlinear transform coding
Ballé, J., Chou, P. A., Minnen, D., Singh, S., Johnston, N., Agustsson, E., Hwang, S. J., and Toderici, G · 2020
Cited alongside, same era.
Learned image compression with discretized gaussian mixture likelihoods and attention modules
Cheng, Z., Sun, H., Takeuchi, M., and Katto, J · 2020
Cited alongside, same era.
The open images dataset v4: Unified image classification, object detection, and visual relationship detection at scale
Kuznetsova, A., Rom, H., Alldrin, N., Uijlings, J., Krasin, I., Pont-Tuset, J., Kamali, S., Popov, S., Malloci, M., Kolesnikov, A., et al · 2020
Cited alongside, same era.
High-fidelity generative image compression
xformers: A modular and hackable transformer modelling library
Lefaudeux, B., Massa, F., Liskovich, D., Xiong, W., Caggiano, V., Naren, S., Xu, M., Hu, J., Tintore, M., Zhang, S., Labatut, P., and Haziza, D · 2022
Later among the works it cites.
Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation
Li, J., Li, D., Xiong, C., and Hoi, S · 2022
Later among the works it cites.
Extreme generative image compression by learning text embedding from diffusion models
Pan, Z., Zhou, X., and Tian, H · 2022
Later among the works it cites.
Hierarchical text-conditional image generation with clip latents, 2022
Ramesh, A., Dhariwal, P., Nichol, A., Chu, C., and Chen, M · 2022
Later among the works it cites.
High-resolution image synthesis with latent diffusion models
Rombach, R., Blattmann, A., Lorenz, D., Esser, P., and Ommer, B · 2022
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Mentzer, F., Toderici, G. D., Tschannen, M., and Agustsson, E · 2020
Cited alongside, same era.
High-fidelity performance metrics for generative models in pytorch, 2020
Obukhov, A., Seitzer, M., Wu, P.-W., Zhydenko, S., Kyl, J., and Lin, E. Y.-J · 2020
Cited alongside, same era.
URL https://clic.compression.cc/2021/index.html
Clic 2021: Challenge on learned image compression · 2021
Cited alongside, same era.
Cogview: Mastering text-to-image generation via transformers
Ding, M., Yang, Z., Hong, W., Zheng, W., Zhou, C., Yin, D., Lin, J., Zou, X., Shao, Z., Yang, H., and Tang, J · 2021
Cited alongside, same era.
Stylegan-nada: Clip-guided domain adaptation of image generators, 2021
Gal, R., Patashnik, O., Maron, H., Chechik, G., and Cohen-Or, D · 2021
Cited alongside, same era.
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
Cited alongside, same era.
Zero-shot text-to-image generation
Ramesh, A., Pavlov, M., Goh, G., Gray, S., Voss, C., Radford, A., Chen, M., and Sutskever, I · 2021
Cited alongside, same era.
From show to tell: A survey on deep learning-based image captioning
Stefanini, M., Cornia, M., Baraldi, L., Cascianelli, S., Fiameni, G., and Cucchiara, R · 2022
Later among the works it cites.
Lossy compression with gaussian diffusion
Theis, L., Salimans, T., Hoffman, M. D., and Mentzer, F · 2022
Later among the works it cites.
Diffusers: State-of-the-art diffusion models
von Platen, P., Patil, S., Lozhkov, A., Cuenca, P., Lambert, N., Rasul, K., Davaadorj, M., and Wolf, T · 2022
Later among the works it cites.
Lossy image compression with conditional diffusion models
Yang, R. and Mandt, S · 2022
Later among the works it cites.
Toward textual transform coding
Weissman, T · 2023
Closest in time.
Hard prompts made easy: Gradient-based discrete optimization for prompt tuning and discovery
Wen, Y., Jain, N., Kirchenbauer, J., Goldblum, M., Geiping, J., and Goldstein, T · 2023
Closest in time.
Adding conditional control to text-to-image diffusion models
Zhang, L. and Agrawala, M · 2023
Closest in time.