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Videos depict the change of complex dynamical systems over time in the form of discrete image sequences.
J. R. Dormand and P. J. Prince, “A family of embedded runge-kutta formulae,”
1980
Earlier work this paper cites.
Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, “Image quality assessment: from error visibility to structural similarity,”
2004
Earlier work this paper cites.
Q. Huynh-Thu and M. Ghanbari, “Scope of validity of psnr in image/video quality assessment,”
2008
Earlier work this paper cites.
A. Hore and D. Ziou, “Image quality metrics: Psnr vs. ssim,” in
2010
Earlier work this paper cites.
Y. Yang, Y. Li, C. Fermuller, and Y. Aloimonos, “Robot learning manipulation action plans by” watching” unconstrained videos from the world wide web,” in
2015
Earlier work this paper cites.
C. Vondrick, H. Pirsiavash, and A. Torralba, “Generating videos with scene dynamics,”
2016
Earlier work this paper cites.
K. He, X. Zhang, S. Ren, and J. Sun, “Deep residual learning for image recognition,” in
2016
Earlier work this paper cites.
2016
Earlier work this paper cites.
M. Saito, E. Matsumoto, and S. Saito, “Temporal generative adversarial nets with singular value clipping,” in
2017
Earlier work this paper cites.
G. Mittal, T. Marwah, and V. N. Balasubramanian, “Sync-draw: Automatic video generation using deep recurrent attentive architectures,” in
2017
Earlier work this paper cites.
A. Van Den Oord, O. Vinyals,
2017
Earlier work this paper cites.
J. Xie, S.-C. Zhu, and Y. Nian Wu, “Synthesizing dynamic patterns by spatial-temporal generative convnet,” in
2017
Earlier work this paper cites.
J. Johnson, B. Hariharan, L. Van Der Maaten, L. Fei-Fei, C. Lawrence Zitnick, and R. Girshick, “Clevr: A diagnostic dataset for compositional language and elementary visual reasoning,” in
2017
Earlier work this paper cites.
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, Ł. Kaiser, and I. Polosukhin, “Attention is all you need,”
2017
Earlier work this paper cites.
M. Heusel, H. Ramsauer, T. Unterthiner, B. Nessler, and S. Hochreiter, “Gans trained by a two time-scale update rule converge to a local nash equilibrium,”
2017
Earlier work this paper cites.
S. Tulyakov, M.-Y. Liu, X. Yang, and J. Kautz, “Mocogan: Decomposing motion and content for video generation,” in
2018
Earlier work this paper cites.
Z. Hao, X. Huang, and S. Belongie, “Controllable video generation with sparse trajectories,” in
2018
Earlier work this paper cites.
CRC press, 2018
S. H. Strogatz, · 2018
Earlier work this paper cites.
R. T. Chen, Y. Rubanova, J. Bettencourt, and D. K. Duvenaud, “Neural ordinary differential equations,”
2018
Cited alongside, same era.
2018
Cited alongside, same era.
2018
Cited alongside, same era.
J. Pan, C. Wang, X. Jia, J. Shao, L. Sheng, J. Yan, and X. Wang, “Video generation from single semantic label map,” in
2019
Cited alongside, same era.
M. Jin, Z. Hu, and P. Favaro, “Learning to extract flawless slow motion from blurry videos,” in
2019
Cited alongside, same era.
H. Zhang, X. Gao, J. Unterman, and T. Arodz, “Approximation capabilities of neural odes and invertible residual networks,” in
2020
Later among the works it cites.
C. Choi, J. H. Choi, J. Li, and S. Malla, “Shared cross-modal trajectory prediction for autonomous driving,” in
2021
Later among the works it cites.
Y. Chen, F. Rong, S. Duggal, S. Wang, X. Yan, S. Manivasagam, S. Xue, E. Yumer, and R. Urtasun, “Geosim: Realistic video simulation via geometry-aware composition for self-driving,” in
2021
Later among the works it cites.
2021
Later among the works it cites.
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2019
Cited alongside, same era.
J. Xie, S.-C. Zhu, and Y. N. Wu, “Learning energy-based spatial-temporal generative convnets for dynamic patterns,”
2019
Cited alongside, same era.
Y. Rubanova, R. T. Chen, and D. K. Duvenaud, “Latent ordinary differential equations for irregularly-sampled time series,”
2019
Cited alongside, same era.
E. De Brouwer, J. Simm, A. Arany, and Y. Moreau, “Gru-ode-bayes: Continuous modeling of sporadically-observed time series,”
2019
Cited alongside, same era.
C. Yildiz, M. Heinonen, and H. Lahdesmaki, “Ode2vae: Deep generative second order odes with bayesian neural networks,”
2019
Cited alongside, same era.
2019
Cited alongside, same era.
E. Dupont, A. Doucet, and Y. W. Teh, “Augmented neural odes,”
2019
Cited alongside, same era.
2021
Later among the works it cites.
S. Park, K. Kim, J. Lee, J. Choo, J. Lee, S. Kim, and E. Choi, “Vid-ode: Continuous-time video generation with neural ordinary differential equation,” in
2021
Later among the works it cites.
A. Blattmann, T. Milbich, M. Dorkenwald, and B. Ommer, “Understanding object dynamics for interactive image-to-video synthesis,” in
2021
Later among the works it cites.
2021
Later among the works it cites.
N. Li, M. A. Raza, W. Hu, Z. Sun, and R. Fisher, “Object-centric representation learning with generative spatial-temporal factorization,”
2021
Later among the works it cites.
D. Kanaa, V. Voleti, S. E. Kahou, and C. Pal, “Simple video generation using neural odes,”
2021
Later among the works it cites.
2021
Later among the works it cites.
Z. Wang and J.-C. Liu, “Translating math formula images to latex sequences using deep neural networks with sequence-level training,”
2021
Later among the works it cites.
2022
Later among the works it cites.
Y. Hu, C. Luo, and Z. Chen, “Make it move: controllable image-to-video generation with text descriptions,” in
2022
Later among the works it cites.
2022
Later among the works it cites.
A. Zeng, M. Attarian, B. Ichter, K. Choromanski, A. Wong, S. Welker, F. Tombari, A. Purohit, M. Ryoo, V. Sindhwani, J. Lee, V. Vanhoucke, and P. Florence, “Socratic models: Composing zero-shot multimodal reasoning with language,”
2022
Later among the works it cites.
2022
Later among the works it cites.