Fetching the paper…
Reading the bibliography…
Videos are created to express emotion, exchange information, and share experiences.
2012
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. NeurIPS (2014)
2014
Earlier work this paper cites.
2014
Earlier work this paper cites.
2014
Earlier work this paper cites.
Kingma, D.P., Ba, J.: Adam: A method for stochastic optimization. ICLR (2015)
2015
Earlier work this paper cites.
Srivastava, N., Mansimov, E., Salakhudinov, R.: Unsupervised learning of video representations using lstms. In: ICML (2015)
2015
Earlier work this paper cites.
Tran, D., Bourdev, L., Fergus, R., Torresani, L., Paluri, M.: Learning spatiotemporal features with 3d convolutional networks. In: ICCV (2015)
2015
Earlier work this paper cites.
Finn, C., Goodfellow, I., Levine, S.: Unsupervised learning for physical interaction through video prediction. NeurIPS (2016)
2016
Earlier work this paper cites.
Johnson, J., Alahi, A., Fei-Fei, L.: Perceptual losses for real-time style transfer and super-resolution. In: ECCV (2016)
2016
Earlier work this paper cites.
Vondrick, C., Pirsiavash, H., Torralba, A.: Generating videos with scene dynamics. NeurIPS (2016)
2016
Earlier work this paper cites.
Carreira, J., Zisserman, A.: Quo vadis, action recognition? a new model and the kinetics dataset. In: CVPR (2017)
2017
Earlier work this paper cites.
Gemmeke, J.F., Ellis, D.P., Freedman, D., Jansen, A., Lawrence, W., Moore, R.C., Plakal, M., Ritter, M.: Audio set: An ontology and human-labeled dataset for audio events. In: ICASSP (2017)
2017
Earlier work this paper cites.
Kalchbrenner, N., Oord, A., Simonyan, K., Danihelka, I., Vinyals, O., Graves, A., Kavukcuoglu, K.: Video pixel networks. In: ICML (2017)
2017
Earlier work this paper cites.
Luc, P., Neverova, N., Couprie, C., Verbeek, J., LeCun, Y.: Predicting deeper into the future of semantic segmentation. In: ICCV (2017)
2017
Earlier work this paper cites.
Mittal, G., Marwah, T., Balasubramanian, V.N.: Sync-draw: Automatic video generation using deep recurrent attentive architectures. In: MM (2017)
2017
Earlier work this paper cites.
van den Oord, A., Vinyals, O., Kavukcuoglu, K.: Neural discrete representation learning. In: NeurIPS (2017)
2017
Earlier work this paper cites.
Saito, M., Matsumoto, E., Saito, S.: Temporal generative adversarial nets with singular value clipping. In: ICCV (2017)
2017
Earlier work this paper cites.
2017
Earlier work this paper cites.
2018
Earlier work this paper cites.
Brock, A., Donahue, J., Simonyan, K.: Large scale gan training for high fidelity natural image synthesis. In: ICLR (2018)
2018
Earlier work this paper cites.
Fan, A., Lewis, M., Dauphin, Y.: Hierarchical neural story generation (2018)
2018
Earlier work this paper cites.
Gupta, T., Schwenk, D., Farhadi, A., Hoiem, D., Kembhavi, A.: Imagine this! scripts to compositions to videos. In: ECCV (2018)
2018
Earlier work this paper cites.
Jiang, S., de Rijke, M.: Why are sequence-to-sequence models so dull? understanding the low-diversity problem of chatbots. In: EMNLP Workshop (2018)
2018
Earlier work this paper cites.
Karras, T., Aila, T., Laine, S., Lehtinen, J.: Progressive growing of gans for improved quality, stability, and variation. In: ICLR (2018)
2018
Earlier work this paper cites.
Li, Y., Min, M., Shen, D., Carlson, D., Carin, L.: Video generation from text. In: AAAI (2018)
2018
Earlier work this paper cites.
Loshchilov, I., Hutter, F.: Decoupled weight decay regularization. In: International Conference on Learning Representations (2018)
2018
Earlier work this paper cites.
Tulyakov, S., Liu, M.Y., Yang, X., Kautz, J.: Mocogan: Decomposing motion and content for video generation. In: CVPR (June 2018)
2018
Earlier work this paper cites.
Vougioukas, K., Petridis, S., Pantic, M.: End-to-end speech-driven facial animation with temporal gans. BMVC (2018)
2018
Cited alongside, same era.
Wang, T.C., Liu, M.Y., Zhu, J.Y., Liu, G., Tao, A., Kautz, J., Catanzaro, B.: Video-to-video synthesis. In: NeurIPS (2018)
2018
Cited alongside, same era.
Wang, T.C., Liu, M.Y., Zhu, J.Y., Tao, A., Kautz, J., Catanzaro, B.: High-resolution image synthesis and semantic manipulation with conditional gans. In: CVPR (2018)
2018
Cited alongside, same era.
Wu, Y., He, K.: Group normalization. In: ECCV (2018)
2018
Cited alongside, same era.
Xiong, W., Luo, W., Ma, L., Liu, W., Luo, J.: Learning to generate time-lapse videos using multi-stage dynamic generative adversarial networks. In: CVPR (2018)
2018
Cited alongside, same era.
Saito, M., Saito, S., Koyama, M., Kobayashi, S.: Train sparsely, generate densely: Memory-efficient unsupervised training of high-resolution temporal gan. IJCV (2020)
2020
Later among the works it cites.
Sitzmann, V., Martel, J., Bergman, A., Lindell, D., Wetzstein, G.: Implicit neural representations with periodic activation functions. NeurIPS (2020)
2020
Later among the works it cites.
Tancik, M., Srinivasan, P., Mildenhall, B., Fridovich-Keil, S., Raghavan, N., Singhal, U., Ramamoorthi, R., Barron, J., Ng, R.: Fourier features let networks learn high frequency functions in low dimensional domains. NeurIPS (2020)
2020
Later among the works it cites.
Weissenborn, D., Täckström, O., Uszkoreit, J.: Scaling autoregressive video models. In: ICLR (2020)
2020
Later among the works it cites.
Alsallakh, B., Kokhlikyan, N., Miglani, V., Yuan, J., Reblitz-Richardson, O.: Mind the pad – CNNs can develop blind spots. In: ICLR (2021)
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
2018
Cited alongside, same era.
Balaji, Y., Min, M.R., Bai, B., Chellappa, R., Graf, H.P.: Conditional gan with discriminative filter generation for text-to-video synthesis. In: IJCAI (2019)
2019
Cited alongside, same era.
2019
Cited alongside, same era.
Cobbe, K., Klimov, O., Hesse, C., Kim, T., Schulman, J.: Quantifying generalization in reinforcement learning. In: ICML (2019)
2019
Cited alongside, same era.
Deng, K., Fei, T., Huang, X., Peng, Y.: Irc-gan: Introspective recurrent convolutional gan for text-to-video generation. In: IJCAI (2019)
2019
Cited alongside, same era.
Islam, M.A., Jia, S., Bruce, N.D.: How much position information do convolutional neural networks encode? In: ICLR (2019)
2019
Cited alongside, same era.
Karras, T., Laine, S., Aila, T.: A style-based generator architecture for generative adversarial networks. In: CVPR (2019)
2019
Cited alongside, same era.
2021
Later among the works it cites.
2021
Later among the works it cites.
Esser, P., Rombach, R., Ommer, B.: Taming transformers for high-resolution image synthesis. In: CVPR (2021)
2021
Later among the works it cites.
Karras, T., Aittala, M., Laine, S., Härkönen, E., Hellsten, J., Lehtinen, J., Aila, T.: Alias-free generative adversarial networks. NeurIPS (2021)
2021
Later among the works it cites.
Le Moing, G., Ponce, J., Schmid, C.: Ccvs: Context-aware controllable video synthesis. NeurIPS (2021)
2021
Later among the works it cites.
2021
Later among the works it cites.
Menapace, W., Lathuilière, S., Tulyakov, S., Siarohin, A., Ricci, E.: Playable video generation. In: CVPR (2021)
2021
Later among the works it cites.
Munoz, A., Zolfaghari, M., Argus, M., Brox, T.: Temporal shift gan for large scale video generation. In: WACV (2021)
2021
Later among the works it cites.
Park, S., Kim, K., Lee, J., Choo, J., Lee, J., Kim, S., Choi, Y.: Vid-ode: Continuous-time video generation with neural ordinary differential equation. In: AAAI. AAAI (2021)
2021
Later among the works it cites.
Radford, A., Kim, J.W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., et al.: Learning transferable visual models from natural language supervision. In: ICML (2021)
2021
Later among the works it cites.
2021
Later among the works it cites.
2021
Later among the works it cites.
Tian, Y., Ren, J., Chai, M., Olszewski, K., Peng, X., Metaxas, D.N., Tulyakov, S.: A good image generator is what you need for high-resolution video synthesis. In: ICLR (2021)
2021
Later among the works it cites.
2021
Later among the works it cites.
2021
Later among the works it cites.
Xu, R., Wang, X., Chen, K., Zhou, B., Loy, C.C.: Positional encoding as spatial inductive bias in gans. In: CVPR (2021)
2021
Later among the works it cites.
2021
Later among the works it cites.
Yu, S., Tack, J., Mo, S., Kim, H., Kim, J., Ha, J.W., Shin, J.: Generating videos with dynamics-aware implicit generative adversarial networks. In: ICLR (2021)
2021
Later among the works it cites.
2022
Closest in time.
2022
Closest in time.
2022
Closest in time.
2022
Closest in time.