Fetching the paper…
Reading the bibliography…
We present a method for transferring the artistic features of an arbitrary style image to a 3D scene.
2014
Earlier work this paper cites.
2016
Earlier work this paper cites.
Gatys, L.A., Ecker, A.S., Bethge, M.: Image style transfer using convolutional neural networks. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 2414–2423 (2016)
2016
Earlier work this paper cites.
Li, C., Wand, M.: Combining markov random fields and convolutional neural networks for image synthesis. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 2479–2486 (2016)
2016
Earlier work this paper cites.
Chen, D., Liao, J., Yuan, L., Yu, N., Hua, G.: Coherent online video style transfer. In: Proceedings of the IEEE International Conference on Computer Vision. pp. 1105–1114 (2017)
2017
Earlier work this paper cites.
Huang, H., Wang, H., Luo, W., Ma, L., Jiang, W., Zhu, X., Li, Z., Liu, W.: Real-time neural style transfer for videos. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 783–791 (2017)
2017
Earlier work this paper cites.
Huang, X., Belongie, S.: Arbitrary style transfer in real-time with adaptive instance normalization. In: Proceedings of the IEEE international conference on computer vision. pp. 1501–1510 (2017)
2017
Earlier work this paper cites.
Knapitsch, A., Park, J., Zhou, Q.Y., Koltun, V.: Tanks and temples: Benchmarking large-scale scene reconstruction. ACM Transactions on Graphics 36
2017
Earlier work this paper cites.
Li, Y., Fang, C., Yang, J., Wang, Z., Lu, X., Yang, M.H.: Diversified texture synthesis with feed-forward networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 3920–3928 (2017)
2017
Earlier work this paper cites.
Li, Y., Fang, C., Yang, J., Wang, Z., Lu, X., Yang, M.H.: Universal style transfer via feature transforms. Advances in neural information processing systems 30
2017
Earlier work this paper cites.
Liao, J., Yao, Y., Yuan, L., Hua, G., Kang, S.B.: Visual attribute transfer through deep image analogy. ACM Trans. Graph. (2017)
2017
Earlier work this paper cites.
Luan, F., Paris, S., Shechtman, E., Bala, K.: Deep photo style transfer. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 4990–4998 (2017)
2017
Earlier work this paper cites.
2017
Earlier work this paper cites.
Tsai, Y.H., Shen, X., Lin, Z., Sunkavalli, K., Lu, X., Yang, M.H.: Deep image harmonization. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 3789–3797 (2017)
2017
Earlier work this paper cites.
Gu, S., Chen, C., Liao, J., Yuan, L.: Arbitrary style transfer with deep feature reshuffle. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 8222–8231 (2018)
2018
Earlier work this paper cites.
Luan, F., Paris, S., Shechtman, E., Bala, K.: Deep painterly harmonization. Computer Graphics Forum 37
2018
Earlier work this paper cites.
Mechrez, R., Talmi, I., Zelnik-Manor, L.: The contextual loss for image transformation with non-aligned data. In: Proceedings of the European conference on computer vision (ECCV). pp. 768–783 (2018)
2018
Earlier work this paper cites.
Ruder, M., Dosovitskiy, A., Brox, T.: Artistic style transfer for videos and spherical images. International Journal of Computer Vision 126
2018
Cited alongside, same era.
Sheng, L., Lin, Z., Shao, J., Wang, X.: Avatar-net: Multi-scale zero-shot style transfer by feature decoration. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 8242–8250 (2018)
2018
Cited alongside, same era.
Jing, Y., Yang, Y., Feng, Z., Ye, J., Yu, Y., Song, M.: Neural style transfer: A review. IEEE transactions on visualization and computer graphics 26
2019
Cited alongside, same era.
Kolkin, N., Salavon, J., Shakhnarovich, G.: Style transfer by relaxed optimal transport and self-similarity. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 10051–10060 (2019)
2019
Cited alongside, same era.
Chen, A., Xu, Z., Zhao, F., Zhang, X., Xiang, F., Yu, J., Su, H.: MVSNeRF: Fast generalizable radiance field reconstruction from multi-view stereo. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 14124–14133 (2021)
2021
Later among the works it cites.
Heitz, E., Vanhoey, K., Chambon, T., Belcour, L.: A sliced wasserstein loss for neural texture synthesis. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 9412–9420 (2021)
2021
Later among the works it cites.
2021
Later among the works it cites.
Huang, H.P., Tseng, H.Y., Saini, S., Singh, M., Yang, M.H.: Learning to stylize novel views. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 13869–13878 (2021)
2021
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Park, D.Y., Lee, K.H.: Arbitrary style transfer with style-attentional networks. In: proceedings of the IEEE/CVF conference on computer vision and pattern recognition. pp. 5880–5888 (2019)
2019
Cited alongside, same era.
Yao, Y., Ren, J., Xie, X., Liu, W., Liu, Y.J., Wang, J.: Attention-aware multi-stroke style transfer. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 1467–1475 (2019)
2019
Cited alongside, same era.
Chiu, T.Y., Gurari, D.: Iterative feature transformation for fast and versatile universal style transfer. In: European Conference on Computer Vision. pp. 169–184. Springer (2020)
2020
Cited alongside, same era.
2020
Cited alongside, same era.
Liu, L., Gu, J., Zaw Lin, K., Chua, T.S., Theobalt, C.: Neural sparse voxel fields. Advances in Neural Information Processing Systems 33
2020
Cited alongside, same era.
Mildenhall, B., Srinivasan, P.P., Tancik, M., Barron, J.T., Ramamoorthi, R., Ng, R.: Nerf: Representing scenes as neural radiance fields for view synthesis. In: European conference on computer vision. pp. 405–421. Springer (2020)
2020
Cited alongside, same era.
Wang, W., Xu, J., Zhang, L., Wang, Y., Liu, J.: Consistent video style transfer via compound regularization. In: Proceedings of the AAAI Conference on Artificial Intelligence. vol. 34, pp. 12233–12240 (2020)
2020
Cited alongside, same era.
Xia, X., Zhang, M., Xue, T., Sun, Z., Fang, H., Kulis, B., Chen, J.: Joint bilateral learning for real-time universal photorealistic style transfer. In: European Conference on Computer Vision. pp. 327–342. Springer (2020)
2020
Cited alongside, same era.
Liu, S., Lin, T., He, D., Li, F., Wang, M., Li, X., Sun, Z., Li, Q., Ding, E.: Adaattn: Revisit attention mechanism in arbitrary neural style transfer. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 6649–6658 (2021)
2021
Later among the works it cites.
2021
Later among the works it cites.
2021
Later among the works it cites.
Xia, X., Xue, T., Lai, W.s., Sun, Z., Chang, A., Kulis, B., Chen, J.: Real-time localized photorealistic video style transfer. In: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision. pp. 1089–1098 (2021)
2021
Later among the works it cites.
Yin, K., Gao, J., Shugrina, M., Khamis, S., Fidler, S.: 3dstylenet: Creating 3d shapes with geometric and texture style variations. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 12456–12465 (2021)
2021
Later among the works it cites.
Yu, A., Li, R., Tancik, M., Li, H., Ng, R., Kanazawa, A.: Plenoctrees for real-time rendering of neural radiance fields. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 5752–5761 (2021)
2021
Later among the works it cites.
Yu, A., Ye, V., Tancik, M., Kanazawa, A.: pixelnerf: Neural radiance fields from one or few images. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 4578–4587 (2021)
2021
Later among the works it cites.
Barron, J.T., Mildenhall, B., Verbin, D., Srinivasan, P.P., Hedman, P.: Mip-nerf 360: Unbounded anti-aliased neural radiance fields. CVPR (2022)
2022
Closest in time.
Chen, A., Xu, Z., Geiger, A., , Yu, J., Su, H.: Tensorf: Tensorial radiance fields (2022)
2022
Closest in time.
Chiang, P.Z., Tsai, M.S., Tseng, H.Y., Lai, W.S., Chiu, W.C.: Stylizing 3d scene via implicit representation and hypernetwork. In: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision. pp. 1475–1484 (2022)
2022
Closest in time.
Kolkin, N., Kucera, M., Paris, S., Sykora, D., Shechtman, E., Shakhnarovich, G.: Neural neighbor style transfer. arXiv e-prints pp. arXiv–2203 (2022)
2022
Closest in time.
Niemeyer, M., Barron, J.T., Mildenhall, B., Sajjadi, M.S.M., Geiger, A., Radwan, N.: Regnerf: Regularizing neural radiance fields for view synthesis from sparse inputs. In: Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) (2022)
2022
Closest in time.