Fetching the paper…
Reading the bibliography…
We introduce a new encoder-decoder GAN model, FutureGAN, that predicts future frames of a video sequence conditioned on a sequence of past frames.
Two-Frame Motion Estimation Based on Polynomial Expansion
G. Farnebäck · 2003
Earlier work this paper cites.
Recognizing Human AAction: A Local SVM Approach
C. Schüldt, I. Laptev, and B. Caputo · 2004
Earlier work this paper cites.
ImageNet Classification with Deep Convolutional Neural Networks
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
Earlier work this paper cites.
Generative Adversarial Networks
I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio · 2014
Earlier work this paper cites.
Video (Language) Modeling: A Baseline for generative Models of natural Videos
M.’A. Ranzato, A. Szlam, J. Bruna, M. Mathieu, R. Collobert, and S. Chopra · 2014
Earlier work this paper cites.
Learning to Linearize Under Uncertainty
R. Goroshin, M. Mathieu, and Y. LeCun · 2015
Earlier work this paper cites.
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
K. He, X. Zhang, S. Ren, and J. Sun · 2015
Earlier work this paper cites.
Adam: A Method for Stochastic Optimization
D. P. Kingma and J. Ba · 2015
Earlier work this paper cites.
Action-Conditional Video Prediction using Deep Networks in Atari Games
J. Oh, X. Guo, H. Lee, R. L. Lewis, and S. Singh · 2015
Earlier work this paper cites.
Unsupervised Learning of Video Representation using LSTMs
N. Srivastava, E. Mansimov, and R. Salakhudinov · 2015
Earlier work this paper cites.
Learning Spatiotemporal Features with 3D Convolutional Networks
D. Tran, L. Bourdev, R. Fergus, L. Torresani, and M. Paluri · 2015
Earlier work this paper cites.
The Cityscapes Dataset for Semantic Urban Scene Understanding
M. Cordts, M. Omran, S. Ramos, T. Rehfeld, M. Enzweiler, R. Benenson, U. Franke, S. Roth, and B. Schiele · 2016
Earlier work this paper cites.
Dynamic Filter Networks
B. De Brabandere, X. Jia, T. Tuytelaars, and L. Van Gool · 2016
Earlier work this paper cites.
Unsupervised Learning for Physical Interaction through Video Prediction
C. Finn, I. Goodfellow, and S. Levine · 2016
Earlier work this paper cites.
Unsupervised Learning of Visual Structure using Predictive Generative Networks
W. Lotter, G. Kreiman, and D. Cox · 2016
Earlier work this paper cites.
Deep multi-scale video prediction beyond mean square error
M. Mathieu, C. Couprie, and Y. LeCun · 2016
Earlier work this paper cites.
Spatio-Temporal Video Autoencoder with Differentiable Memory
V. Patraucean, A. Handa, and R. Cipolla · 2016
Cited alongside, same era.
Improved Techniques for Training GANs
T. Salimans, I. J. Goodfellow, W. Zaremba, V. Cheung, A. Radford, and X. Chen · 2016
Cited alongside, same era.
Generating Videos with Scene Dynamics
C. Vondrick, H. Pirsiavash, and A. Torralba · 2016
Cited alongside, same era.
One-Step Time-Dependent Future Video Frame Prediction with a Convolutional Encoder-Decoder Neural Network
V. Vukoti, A.-L. Pintea, C. Raymond, G. Gravier, and J. Van Gemert · 2016
Cited alongside, same era.
An Uncertain Future: Forecasting from Static Images using Variational Autoencoders
J. Walker, C. Doersch, A. Gupta, and M. Hebert · 2016
Cited alongside, same era.
Visual Dynamics: Probabilistic Future Frame Synthesis via Cross Convolutional Networks
T. Xue, J. Wu, K. L. Bouman, and W. T. Freeman · 2016
Geometry-Based Next Frame Prediction from Monocular Video
R. Mahjourian, M. Wicke, and A. Angelova · 2017
Later among the works it cites.
Temporal Generative Adversarial Nets With Singular Value Clipping
M. Saito, E. Matsumoto, and S. Saito · 2017
Later among the works it cites.
Decomposing Motion and Content for Natural Video Sequence Prediction
R. Villegas, J. Yang, S. Hong, X. Lin, and H. Lee · 2017
Later among the works it cites.
Generating the Future with Adversarial Transformers
C. Vondrick, H. Pirsiavash, and A. Torralba · 2017
Later among the works it cites.
PredRNN: Recurrent Neural Networks for Predictive Learning using Spatiotemporal LSTMs
Y. Wang, M. Long, J. Wang, Z. Gao, and P. S. Yu · 2017
Later among the works it cites.
Visual Forecasting by Imitating Dynamics in Natural Sequences
K.-H. Zeng, W. B. Shen, D.-A. Huang, M. Sun, and J. C. Niebles · 2017
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Temporal Coherency based Criteria for Predicting Video Frames using Deep Multi-stage Generative Adversarial Networks
P. Bhattacharjee and S. Das · 2017
Cited alongside, same era.
Video Imagination from a Single Image with Transformation Generation
B. Chen, W. Wang, J. Wang, and X. Chen · 2017
Cited alongside, same era.
Unsupervised Learning of Disentangled Representations from Video
E. L. Denton and V. Birodkar · 2017
Cited alongside, same era.
Improved Training of Wasserstein GANs
I. Gulrajani, F. Ahmed, M. Arjovsky, V. Dumoulin, and A. Courville · 2017
Cited alongside, same era.
Video Pixel Networks
N. Kalchbrenner, A. van den Oord, K. Simonyan, I. Danihelka, O. Vinyals, A. Graves, and K. Kavukcuoglu · 2017
Cited alongside, same era.
Improving Video Generation for Multi-functional Applications
B. Kratzwald, Z. Huang, D. P. Paudel, , A. Dinesh, and L. Van Gool · 2017
Cited alongside, same era.
Later among the works it cites.
Wasserstein GAN
M. Arjovsky, S. Chitala, and L. Bottou · 2018
Closest in time.
Stochastic Variational Video Prediction
M. Babaeizadeh, C. Finn, D. Erhan, R. H. Campbell, and S. Levine · 2018
Closest in time.
Fully Context-Aware Video Prediction
W. Byeon, Q. Wang, R. K. Srivastava, and P. Koumoutsakos · 2018
Closest in time.
Stochastic Video Generation with a Learned Prior
E. Denton and R. Fergus · 2018
Closest in time.
Controllable Video Generation with Sparse Trajectories
Z. Hao, X. Huang, and S. Belongie · 2018
Closest in time.
Progressive Growing of GANs for Improved Quality, Stability, and Variation
T. Karras, T. Aila, S. Laine, and J. Lehtinen · 2018
Closest in time.
Stochastic Adversarial Video Prediction
A. X. Lee, R. Zhang, F. Ebert, P. Abbeel, C. Finn, and S. Levine · 2018
Closest in time.
Folded Recurrent Neural Networks for Future Video Prediction
M. Oliu, J. Selva, and S. Escalera · 2018
Closest in time.
MoCoGAN: Decomposing Motion and Content for Video Generation
S. Tulyakov, M.-Y. Liu, X. Yang, and J. Kautz · 2018
Closest in time.
Learning to Generate Time-Lapse Videos Using Multi-Stage Dynamic Generative Adversarial Networks
W. Xiong, W. Luo, L. Ma, W. Liu, and J. Luo · 2018
Closest in time.