Fetching the paper…
Reading the bibliography…
This paper proposes an approach that generates multiple 3D human meshes from text.
Hochreiter, S., Schmidhuber, J.: Long short-term memory. Neural computation 9
1997
Earlier work this paper cites.
Hinton, G.E.: Deep belief networks. Scholarpedia 4
2009
Earlier work this paper cites.
Salakhutdinov, R., Hinton, G.: Deep boltzmann machines. In: Artificial intelligence and statistics. pp. 448–455 (2009)
2009
Earlier work this paper cites.
Grabner, H., Gall, J., Van Gool, L.: What makes a chair a chair? In: CVPR 2011. pp. 1529–1536. IEEE (2011)
2011
Earlier work this paper cites.
Gupta, A., Satkin, S., Efros, A.A., Hebert, M.: From 3d scene geometry to human workspace. In: CVPR 2011. pp. 1961–1968. IEEE (2011)
2011
Earlier work this paper cites.
Kingma, D.P., Welling, M.: Auto-encoding variational bayes. arXiv preprint arXiv:1312.6114 (2013)
2013
Earlier work this paper cites.
Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., Bengio, Y.: Generative adversarial nets. Advances in Neural Information Processing Systems 27
2014
Earlier work this paper cites.
Lin, T.Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Dollár, P., Zitnick, C.L.: Microsoft coco: Common objects in context. In: European conference on computer vision. pp. 740–755. Springer (2014)
2014
Earlier work this paper cites.
Lin, T.Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Dollar, P., Zitnick, C.L.: Microsoft coco: common objects in context. In: European Conference on Computer Vision (2014)
2014
Earlier work this paper cites.
Loper, M., Mahmood, N., Romero, J., Pons-Moll, G., Black, M.J.: Smpl: A skinned multi-person linear model. ACM transactions on graphics (TOG) 34
2015
Earlier work this paper cites.
Salakhutdinov, R.: Learning deep generative models. Annual Review of Statistics and Its Application 2
2015
Earlier work this paper cites.
2016
Earlier work this paper cites.
Radford, A., Metz, L., Chintala, S.: Unsupervised representation learning with deep convolutional generative adversarial networks. In: International Conference on Learning Representations (2016)
2016
Earlier work this paper cites.
Reed, S., Akata, Z., Yan, X., Logeswaran, L., Schiele, B., Lee, H.: Generative adversarial text to image synthesis. In: International Conference on Machine Learning (2016)
2016
Earlier work this paper cites.
Reed, S.E., Akata, Z., Mohan, S., Tenka, S., Schiele, B., Lee, H.: Learning what and where to draw. In: Lee, D., Sugiyama, M., Luxburg, U., Guyon, I., Garnett, R. (eds.) Advances in Neural Information Processing Systems. vol. 29. Curran Associates, Inc. (2016), https://proceedings.neurips.cc/paper/2016/file/a8f15eda80c50adb0e71943adc8015cf-Paper.pdf
2016
Earlier work this paper cites.
Reed, S.E., Akata, Z., Mohan, S., Tenka, S., Schiele, B., Lee, H.: Learning what and where to draw. In: Lee, D.D., Sugiyama, M., Luxburg, U.V., Guyon, I., Garnett, R. (eds.) Advances in Neural Information Processing Systems 29, pp. 217–225. Curran Associates, Inc. (2016), http://papers.nips.cc/paper/6111-learning-what-and-where-to-draw.pdf
2016
Cited alongside, same era.
Arjovsky, M., Chintala, S., Bottou, L.: Wasserstein generative adversarial networks. In: International conference on machine learning. pp. 214–223. PMLR (2017)
2017
Cited alongside, same era.
2017
Cited alongside, same era.
Dai, B., Fidler, S., Urtasun, R., Lin, D.: Towards diverse and natural image descriptions via a conditional gan. In: Proceedings of the IEEE International Conference on Computer Vision. pp. 2970–2979 (2017)
2017
Li, X., Liu, S., Kim, K., Wang, X., Yang, M.H., Kautz, J.: Putting humans in a scene: Learning affordance in 3d indoor environments. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (June 2019)
2019
Later among the works it 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: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (June 2019)
2019
Later among the works it cites.
Qiao, T., Zhang, J., Xu, D., Tao, D.: Learn, imagine and create: Text-to-image generation from prior knowledge. In: Wallach, H., Larochelle, H., Beygelzimer, A., d Alche-Buc, F., Fox, E., Garnett, R. (eds.) Advances in Neural Information Processing Systems 32, pp. 887–897. Curran Associates, Inc. (2019)
2019
Later among the works it cites.
Qiao, T., Zhang, J., Xu, D., Tao, D.: Mirrorgan: Learning text-to-image generation by redescription. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 1505–1514 (2019)
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
2017
Cited alongside, same era.
2017
Cited alongside, same era.
Gulrajani, I., Ahmed, F., Arjovsky, M., Dumoulin, V., Courville, A.C.: Improved training of wasserstein gans. In: Advances in Neural Information Processing Systems (2017)
2017
Cited alongside, same era.
2017
Cited alongside, same era.
Ma, L., Jia, X., Sun, Q., Schiele, B., Tuytelaars, T., Van Gool, L.: Pose guided person image generation. In: Advances in Neural Information Processing Systems (2017)
2017
Cited alongside, same era.
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: IEEE International Conference on Computer Vision (2017)
2017
Cited alongside, same era.
2017
Cited alongside, same era.
Kato, H., Ushiku, Y., Harada, T.: Neural 3d mesh renderer. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 3907–3916 (2018)
2018
Cited alongside, same era.
2019
Later among the works it cites.
Tan, H., Liu, X., Li, X., Zhang, Y., Yin, B.: Semantics-enhanced adversarial nets for text-to-image synthesis. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 10501–10510 (2019)
2019
Later among the works it cites.
Zhou, X., Huang, S., Li, B., Li, Y., Li, J., Zhang, Z.: Text guided person image synthesis. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 3663–3672 (2019)
2019
Later among the works it cites.
Zhu, M., Pan, P., Chen, W., Yang, Y.: Dm-gan: Dynamic memory generative adversarial networks for text-to-image synthesis. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 5802–5810 (2019)
2019
Later among the works it cites.
2020
Later among the works it cites.
Tang, H., Bai, S., Zhang, L., Torr, P.H., Sebe, N.: Xinggan for person image generation. In: European Conference on Computer Vision. pp. 717–734. Springer (2020)
2020
Later among the works it cites.
2020
Later among the works it cites.
Zhang, Y., Hassan, M., Neumann, H., Black, M.J., Tang, S.: Generating 3d people in scenes without people. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 6194–6204 (2020)
2020
Later among the works it cites.
Prokudin, S., Black, M.J., Romero, J.: Smplpix: Neural avatars from 3d human models. In: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision. pp. 1810–1819 (2021)
2021
Closest in time.
2021
Closest in time.
Zhang, Y., Briq, R., Tanke, J., Gall, J.: Adversarial synthesis of human pose from text. In: Pattern Recognition: 42nd DAGM German Conference, DAGM GCPR 2020, Tübingen, Germany, September 28–October 1, 2020, Proceedings 42. pp. 145–158. Springer (2021)
2021
Closest in time.