Fetching the paper…
Reading the bibliography…
The state-of-the-art methods for story visualization demonstrate a significant demand for training data and storage, as well as limited flexibility in story presentation, thereby rendering them impractical for real-world applications.
Reed, S., Akata, Z., Yan, X., Logeswaran, L., Schiele, B., Lee, H.: Generative adversarial text to image synthesis. In: International Conference on Machine Learning, pp. 1060–1069 (2016). PMLR
2016
Earlier work this paper cites.
Zhang, H., Xu, T., Li, H., Zhang, S., Wang, X., Huang, X., Metaxas, D.N.: Stackgan: Text to photo-realistic image synthesis with stacked generative adversarial networks. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 5907–5915 (2017)
2017
Earlier work this paper cites.
Bao, J., Chen, D., Wen, F., Li, H., Hua, G.: Cvae-gan: fine-grained image generation through asymmetric training. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 2745–2754 (2017)
2017
Earlier work this paper cites.
Heusel, M., Ramsauer, H., Unterthiner, T., Nessler, B., Hochreiter, S.: Gans trained by a two time-scale update rule converge to a local nash equilibrium. Advances in neural information processing systems 30
2017
Earlier work this paper cites.
Zhang, Z., Xie, Y., Yang, L.: Photographic text-to-image synthesis with a hierarchically-nested adversarial network. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 6199–6208 (2018)
2018
Earlier work this paper cites.
Li, Y., Gan, Z., Shen, Y., Liu, J., Cheng, Y., Wu, Y., Carin, L., Carlson, D., Gao, J.: Storygan: A sequential conditional gan for story visualization. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 6329–6338 (2019)
2019
Earlier work this paper cites.
Li, W., Zhang, P., Zhang, L., Huang, Q., He, X., Lyu, S., Gao, J.: Object-driven text-to-image synthesis via adversarial training. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 12174–12182 (2019)
2019
Earlier work this paper cites.
Li, Y., Gan, Z., Shen, Y., Liu, J., Cheng, Y., Wu, Y., Carin, L., Carlson, D., Gao, J.: Storygan: A sequential conditional gan for story visualization. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 6329–6338 (2019)
2019
Earlier work this paper cites.
Ho, J., Jain, A., Abbeel, P.: Denoising diffusion probabilistic models. Advances in neural information processing systems 33
2020
Earlier work this paper cites.
Li, B., Qi, X., Lukasiewicz, T., Torr, P.H.: Manigan: Text-guided image manipulation. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 7880–7889 (2020)
2020
Earlier work this paper cites.
Song, Y.-Z., Rui Tam, Z., Chen, H.-J., Lu, H.-H., Shuai, H.-H.: Character-preserving coherent story visualization. In: European Conference on Computer Vision, pp. 18–33 (2020). Springer
2020
Earlier work this paper cites.
Li, C., Kong, L., Zhou, Z.: Improved-storygan for sequential images visualization. Journal of Visual Communication and Image Representation 73
2020
Earlier work this paper cites.
2020
Earlier work this paper cites.
Ding, M., Yang, Z., Hong, W., Zheng, W., Zhou, C., Yin, D., Lin, J., Zou, X., Shao, Z., Yang, H., et al
2021
Earlier work this paper cites.
Ramesh, A., Pavlov, M., Goh, G., Gray, S., Voss, C., Radford, A., Chen, M., Sutskever, I.: Zero-shot text-to-image generation. In: International Conference on Machine Learning, pp. 8821–8831 (2021). PMLR
2021
Earlier work this paper cites.
Nichol, A.Q., Dhariwal, P.: Improved denoising diffusion probabilistic models. In: International Conference on Machine Learning, pp. 8162–8171 (2021). PMLR
2021
Earlier work this paper cites.
Dhariwal, P., Nichol, A.: Diffusion models beat gans on image synthesis. Advances in neural information processing systems 34
2021
Earlier work this paper cites.
2021
Earlier work this paper cites.
2021
Cited alongside, same era.
Ruan, S., Zhang, Y., Zhang, K., Fan, Y., Tang, F., Liu, Q., Chen, E.: Dae-gan: Dynamic aspect-aware gan for text-to-image synthesis. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 13960–13969 (2021)
2021
Cited alongside, same era.
2021
Cited alongside, same era.
Ghiasi, G., Cui, Y., Srinivas, A., Qian, R., Lin, T.-Y., Cubuk, E.D., Le, Q.V., Zoph, B.: Simple copy-paste is a strong data augmentation method for instance segmentation. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 2918–2928 (2021)
2021
2023
Closest in time.
Ruiz, N., Li, Y., Jampani, V., Pritch, Y., Rubinstein, M., Aberman, K.: Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 22500–22510 (2023)
2023
Closest in time.
2023
Closest in time.
Kumari, N., Zhang, B., Zhang, R., Shechtman, E., Zhu, J.-Y.: Multi-concept customization of text-to-image diffusion. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 1931–1941 (2023)
2023
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Ding, M., Zheng, W., Hong, W., Tang, J.: Cogview2: Faster and better text-to-image generation via hierarchical transformers. Advances in Neural Information Processing Systems 35
2022
Cited alongside, same era.
Ho, J., Salimans, T.: Classifier-free diffusion guidance. arXiv preprint arXiv:2207.12598 (2022)
2022
Cited alongside, same era.
2022
Cited alongside, same era.
Rombach, R., Blattmann, A., Lorenz, D., Esser, P., Ommer, B.: High-resolution image synthesis with latent diffusion models. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 10684–10695 (2022)
2022
Cited alongside, same era.
Maharana, A., Hannan, D., Bansal, M.: Storydall-e: Adapting pretrained text-to-image transformers for story continuation. In: European Conference on Computer Vision, pp. 70–87 (2022). Springer
2022
Cited alongside, same era.
2022
Cited alongside, same era.
Saharia, C., Chan, W., Saxena, S., Li, L., Whang, J., Denton, E.L., Ghasemipour, K., Gontijo Lopes, R., Karagol Ayan, B., Salimans, T., et al
2022
Cited alongside, same era.
Li, B.: Word-level fine-grained story visualization. In: European Conference on Computer Vision, pp. 347–362 (2022). Springer
2022
Cited alongside, same era.
Closest in time.
2023
Closest in time.
2023
Closest in time.
Ahn, D., Kim, D., Song, G., Kim, S.H., Lee, H., Kang, D., Choi, J.: Story visualization by online text augmentation with context memory. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 3125–3135 (2023)
2023
Closest in time.
2023
Closest in time.
Yang, B., Gu, S., Zhang, B., Zhang, T., Chen, X., Sun, X., Chen, D., Wen, F.: Paint by example: Exemplar-based image editing with diffusion models. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 18381–18391 (2023)
2023
Closest in time.
Deng, J., Fan, D., Qiu, X., Zhou, F.: Improving crowded object detection via copy-paste. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 37, pp. 497–505 (2023)
2023
Closest in time.
Yu, C., Zhou, Q., Li, J., Yuan, J., Wang, Z., Wang, F.: Foundation model drives weakly incremental learning for semantic segmentation. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 23685–23694 (2023)
2023
Closest in time.
Yoon, J., Choi, M.-K.: Exploring video frame redundancies for efficient data sampling and annotation in instance segmentation. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 3307–3316 (2023)
2023
Closest in time.
Brooks, T., Holynski, A., Efros, A.A.: Instructpix2pix: Learning to follow image editing instructions. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 18392–18402 (2023)
2023
Closest in time.
Mokady, R., Hertz, A., Aberman, K., Pritch, Y., Cohen-Or, D.: Null-text inversion for editing real images using guided diffusion models. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 6038–6047 (2023)
2023
Closest in time.
Yang, B., Gu, S., Zhang, B., Zhang, T., Chen, X., Sun, X., Chen, D., Wen, F.: Paint by example: Exemplar-based image editing with diffusion models. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 18381–18391 (2023)
2023
Closest in time.
2023
Closest in time.
Parmar, G., Kumar Singh, K., Zhang, R., Li, Y., Lu, J., Zhu, J.-Y.: Zero-shot image-to-image translation. In: ACM SIGGRAPH 2023 Conference Proceedings, pp. 1–11 (2023)
2023
Closest in time.