Fetching the paper…
Reading the bibliography…
We propose a weakly-supervised approach for conditional image generation of complex scenes where a user has fine control over objects appearing in the scene.
Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., Bengio, Y.: Generative adversarial nets. In: Neural Information Processing Systems. pp. 2672–2680 (2014)
2014
Earlier work this paper cites.
Kingma, D.P., Welling, M.: Auto-encoding variational Bayes. In: International Conference on Learning Representations (ICLR) (2014)
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 (ECCV). pp. 740–755. Springer (2014)
2014
Earlier work this paper cites.
2014
Earlier work this paper cites.
2015
Earlier work this paper cites.
Kiros, R., Zhu, Y., Salakhutdinov, R.R., Zemel, R., Urtasun, R., Torralba, A., Fidler, S.: Skip-thought vectors. In: Neural Information Processing Systems. pp. 3294–3302 (2015)
2015
Earlier work this paper cites.
Ren, S., He, K., Girshick, R., Sun, J.: Faster R-CNN: Towards real-time object detection with region proposal networks. In: Neural Information Processing Systems. pp. 91–99 (2015)
2015
Earlier work this paper cites.
Srivastava, R.K., Greff, K., Schmidhuber, J.: Highway networks. In: ICML Deep Learning Workshop (2015)
2015
Earlier work this paper cites.
2016
Earlier work this paper cites.
Reed, S., van den Oord, A., Kalchbrenner, N., Bapst, V., Botvinick, M., de Freitas, N.: Generating interpretable images with controllable structure. OpenReview (2016)
2016
Earlier work this paper cites.
Szegedy, C., Vanhoucke, V., Ioffe, S., Shlens, J., Wojna, Z.: Rethinking the inception architecture for computer vision. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pp. 2818–2826 (2016)
2016
Earlier work this paper cites.
Yan, X., Yang, J., Sohn, K., Lee, H.: Attribute2image: Conditional image generation from visual attributes. In: European Conference on Computer Vision (ECCV). pp. 776–791. Springer (2016)
2016
Earlier work this paper cites.
Chen, Q., Koltun, V.: Photographic image synthesis with cascaded refinement networks. In: IEEE International Conference on Computer Vision (ICCV). pp. 1511–1520 (2017)
2017
Earlier work this paper cites.
He, K., Gkioxari, G., Dollár, P., Girshick, R.: Mask R-CNN. In: IEEE International Conference on Computer Vision (ICCV). pp. 2961–2969 (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. In: Neural Information Processing Systems. pp. 6626–6637 (2017)
2017
Earlier work this paper cites.
Isola, P., Zhu, J.Y., Zhou, T., Efros, A.A.: Image-to-image translation with conditional adversarial networks. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pp. 1125–1134 (2017)
2017
Earlier work this paper cites.
Krishna, R., Zhu, Y., Groth, O., Johnson, J., Hata, K., Kravitz, J., Chen, S., Kalantidis, Y., Li, L.J., Shamma, D.A., Bernstein, M.S., Fei-Fei, L.: Visual genome: Connecting language and vision using crowdsourced dense image annotations. International Journal of Computer Vision (IJCV) 123
2017
Earlier work this paper cites.
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, Ł., Polosukhin, I.: Attention is all you need. In: Neural Information Processing Systems. pp. 5998–6008 (2017)
2017
Earlier work this paper cites.
Yang, J., Kannan, A., Batra, D., Parikh, D.: LR-GAN: layered recursive generative adversarial networks for image generation. In: International Conference on Learning Representations (ICLR) (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 (ICCV). pp. 5907–5915 (2017)
2017
Cited alongside, same era.
Zhu, J.Y., Park, T., Isola, P., Efros, A.A.: Unpaired image-to-image translation using cycle-consistent adversarial networks. In: IEEE International Conference on Computer Vision (ICCV). pp. 2223–2232 (2017)
2017
Cited alongside, same era.
Caesar, H., Uijlings, J., Ferrari, V.: COCO-Stuff: Thing and stuff classes in context. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2018)
2018
Cited alongside, same era.
Zhang, H., Xu, T., Li, H., Zhang, S., Wang, X., Huang, X., Metaxas, D.N.: StackGAN++: Realistic image synthesis with stacked generative adversarial networks. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 41
2018
Later among the works it cites.
Brock, A., Donahue, J., Simonyan, K.: Large scale GAN training for high fidelity natural image synthesis. In: International Conference on Learning Representations (ICLR) (2019)
2019
Closest in time.
El-Nouby, A., Sharma, S., Schulz, H., Hjelm, D., El Asri, L., Ebrahimi Kahou, S., Bengio, Y., Taylor, G.W.: Tell, draw, and repeat: Generating and modifying images based on continual linguistic instruction. In: IEEE International Conference on Computer Vision (ICCV) (2019)
2019
Closest in time.
Gupta, A., Dollar, P., Girshick, R.: Lvis: A dataset for large vocabulary instance segmentation. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pp. 5356–5364 (2019)
2019
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Chen, L.C., Papandreou, G., Kokkinos, I., Murphy, K., Yuille, A.L.: Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 40
2018
Cited alongside, same era.
2018
Cited alongside, same era.
2018
Cited alongside, same era.
Hong, S., Yang, D., Choi, J., Lee, H.: Inferring semantic layout for hierarchical text-to-image synthesis. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pp. 7986–7994 (2018)
2018
Cited alongside, same era.
Hu, R., Dollár, P., He, K., Darrell, T., Girshick, R.: Learning to segment every thing. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pp. 4233–4241 (2018)
2018
Cited alongside, same era.
Johnson, J., Gupta, A., Fei-Fei, L.: Image generation from scene graphs. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2018)
2018
Cited alongside, same era.
Karras, T., Aila, T., Laine, S., Lehtinen, J.: Progressive growing of GANs for improved quality, stability, and variation. In: International Conference on Learning Representations (ICLR) (2018)
2018
Cited alongside, same era.
Kilcher, Y., Lucchi, A., Hofmann, T.: Semantic interpolation in implicit models. In: International Conference on Learning Representations (ICLR) (2018)
2018
Cited alongside, same era.
He, Z., Zuo, W., Kan, M., Shan, S., Chen, X.: Attgan: Facial attribute editing by only changing what you want. IEEE Transactions on Image Processing (2019)
2019
Closest in time.
Hinz, T., Heinrich, S., Wermter, S.: Generating multiple objects at spatially distinct locations. In: International Conference on Learning Representations (ICLR) (2019)
2019
Closest in time.
Joseph, K., Pal, A., Rajanala, S., Balasubramanian, V.N.: C4Synth: Cross-caption cycle-consistent text-to-image synthesis. In: IEEE Winter Conference on Applications of Computer Vision (WACV). pp. 358–366. IEEE (2019)
2019
Closest in time.
Karras, T., Laine, S., Aila, T.: A style-based generator architecture for generative adversarial networks. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pp. 4401–4410 (2019)
2019
Closest in time.
Locatello, F., Bauer, S., Lucic, M., Gelly, S., Schölkopf, B., Bachem, O.: Challenging common assumptions in the unsupervised learning of disentangled representations. In: International Conference on Machine Learning (ICML) (2019)
2019
Closest in time.
Mo, S., Cho, M., Shin, J.: Instance-aware image-to-image translation. In: International Conference on Learning Representations (ICLR) (2019)
2019
Closest in time.
Park, T., Liu, M.Y., Wang, T.C., Zhu, J.Y.: Semantic image synthesis with spatially-adaptive normalization. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pp. 2337–2346 (2019)
2019
Closest in time.
Singh, K.K., Ojha, U., Lee, Y.J.: FineGAN: Unsupervised hierarchical disentanglement for fine-grained object generation and discovery. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2019)
2019
Closest in time.
Sun, W., Wu, T.: Image synthesis from reconfigurable layout and style. In: IEEE International Conference on Computer Vision (ICCV). pp. 10531–10540 (2019)
2019
Closest in time.
Turkoglu, M.O., Thong, W., Spreeuwers, L., Kicanaoglu, B.: A layer-based sequential framework for scene generation with GANs. In: Proceedings of the AAAI Conference on Artificial Intelligence. vol. 33, pp. 8901–8908 (2019)
2019
Closest in time.
Yin, G., Liu, B., Sheng, L., Yu, N., Wang, X., Shao, J.: Semantics disentangling for text-to-image generation. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pp. 2327–2336 (2019)
2019
Closest in time.
Zhang, H., Goodfellow, I., Metaxas, D., Odena, A.: Self-attention generative adversarial networks. In: International Conference on Machine Learning (ICML) (2019)
2019
Closest in time.
Zhao, B., Meng, L., Yin, W., Sigal, L.: Image generation from layout. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2019)
2019
Closest in time.