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In this work, we focus on a challenging task: synthesizing multiple imaginary videos given a single image.
Computing two motions from three frames. In Computer Vision, 1990. Proceedings, Third International Conference on
James R Bergen, Peter J Burt, Rajesh Hingorani, and Shmuel Peleg. 1990 · 1990
Earlier work this paper cites.
Layered representation for motion analysis. In Computer Vision and Pattern Recognition, 1993. Proceedings CVPR’93., 1993 IEEE Computer Society Conference on
John YA Wang and Edward H Adelson. 1993 · 1993
Earlier work this paper cites.
High accuracy optical flow estimation based on a theory for warping
Thomas Brox, Andrés Bruhn, Nils Papenberg, and Joachim Weickert. 2004 · 2004
Earlier work this paper cites.
Image quality assessment: from error visibility to structural similarity
Zhou Wang, Alan C Bovik, Hamid R Sheikh, and Eero P Simoncelli. 2004 · 2004
Earlier work this paper cites.
Intra prediction by template matching. In Image Processing, 2006 IEEE International Conference on
Thiow Keng Tan, Choong Seng Boon, and Yoshinori Suzuki. 2006 · 2006
Earlier work this paper cites.
Extracting and composing robust features with denoising autoencoders. In Proceedings of the 25th international conference on Machine learning
Pascal Vincent, Hugo Larochelle, Yoshua Bengio, and Pierre-Antoine Manzagol. 2008 · 2008
Earlier work this paper cites.
Moving gradients: a path-based method for plausible image interpolation
Dhruv Mahajan, Fu-Chung Huang, Wojciech Matusik, Ravi Ramamoorthi, and Peter Belhumeur. 2009 · 2009
Earlier work this paper cites.
Mean squared error: Love it or leave it? A new look at signal fidelity measures
Zhou Wang and Alan C Bovik. 2009 · 2009
Earlier work this paper cites.
Deconvolutional networks. In Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on
Matthew D Zeiler, Dilip Krishnan, Graham W Taylor, and Rob Fergus. 2010 · 2010
Earlier work this paper cites.
Activity forecasting. In European Conference on Computer Vision
Kris M Kitani, Brian D Ziebart, James Andrew Bagnell, and Martial Hebert. 2012 · 2012
Earlier work this paper cites.
No-reference image quality assessment in the spatial domain
Anish Mittal, Anush Krishna Moorthy, and Alan Conrad Bovik. 2012 · 2012
Earlier work this paper cites.
UCF101: A dataset of 101 human actions classes from videos in the wild
Khurram Soomro, Amir Roshan Zamir, and Mubarak Shah. 2012 · 2012
Earlier work this paper cites.
3D convolutional neural networks for human action recognition
Shuiwang Ji, Wei Xu, Ming Yang, and Kai Yu. 2013 · 2013
Earlier work this paper cites.
Auto-encoding variational bayes
Diederik P Kingma and Max Welling. 2013 · 2013
Earlier work this paper cites.
Generative adversarial nets. In Advances in neural information processing systems
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. 2014 · 2014
Earlier work this paper cites.
Max-margin early event detectors
Minh Hoai and Fernando De la Torre. 2014 · 2014
Cited alongside, same era.
A hierarchical representation for future action prediction. In European Conference on Computer Vision
Tian Lan, Tsung-Chuan Chen, and Silvio Savarese. 2014 · 2014
Cited alongside, same era.
Déja vu. In European Conference on Computer Vision
Silvia L Pintea, Jan C van Gemert, and Arnold WM Smeulders. 2014 · 2014
Cited alongside, same era.
Video (language) modeling: a baseline for generative models of natural videos
MarcAurelio Ranzato, Arthur Szlam, Joan Bruna, Michael Mathieu, Ronan Collobert, and Sumit Chopra. 2014 · 2014
Cited alongside, same era.
Sequence to sequence learning with neural networks. In Advances in neural information processing systems
Ilya Sutskever, Oriol Vinyals, and Quoc V Le. 2014 · 2014
Cited alongside, same era.
Dynamic filter networks. In Neural Information Processing Systems (NIPS)
Bert De Brabandere, Xu Jia, Tinne Tuytelaars, and Luc Van Gool. 2016 · 2016
Later among the works it cites.
Unsupervised learning for physical interaction through video prediction. In Advances In Neural Information Processing Systems
Chelsea Finn, Ian Goodfellow, and Sergey Levine. 2016 · 2016
Later among the works it cites.
Identity mappings in deep residual networks. In European Conference on Computer Vision
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016 · 2016
Later among the works it cites.
Nal Kalchbrenner, Aaron van den Oord, Karen Simonyan, Ivo Danihelka, Oriol Vinyals, Alex Graves, and Koray Kavukcuoglu. 2016 · 2016
Later among the works it cites.
Generating videos with scene dynamics. In Advances In Neural Information Processing Systems
Carl Vondrick, Hamed Pirsiavash, and Antonio Torralba. 2016 · 2016
Later among the works it cites.
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Patch to the future: Unsupervised visual prediction. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition
Jacob Walker, Abhinav Gupta, and Martial Hebert. 2014 · 2014
Cited alongside, same era.
Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks. In Advances in neural information processing systems
Emily L Denton, Soumith Chintala, Rob Fergus, and others. 2015 · 2015
Cited alongside, same era.
DRAW: A recurrent neural network for image generation
Karol Gregor, Ivo Danihelka, Alex Graves, Danilo Jimenez Rezende, and Daan Wierstra. 2015 · 2015
Cited alongside, same era.
Deep multi-scale video prediction beyond mean square error
Michael Mathieu, Camille Couprie, and Yann LeCun. 2015 · 2015
Cited alongside, same era.
Unsupervised representation learning with deep convolutional generative adversarial networks
Alec Radford, Luke Metz, and Soumith Chintala. 2015 · 2015
Cited alongside, same era.
Unsupervised Learning of Video Representations using LSTMs.. In ICML
Nitish Srivastava, Elman Mansimov, and Ruslan Salakhutdinov. 2015 · 2015
Cited alongside, same era.
A note on the evaluation of generative models
Lucas Theis, Aäron van den Oord, and Matthias Bethge. 2015 · 2015
Cited alongside, same era.
An uncertain future: Forecasting from static images using variational autoencoders. In European Conference on Computer Vision
Jacob Walker, Carl Doersch, Abhinav Gupta, and Martial Hebert. 2016 · 2016
Later among the works it cites.
Synthesizing Dynamic Textures and Sounds by Spatial-Temporal Generative ConvNet
Jianwen Xie, Song-Chun Zhu, and Ying Nian Wu. 2016b · 2016
Later among the works it cites.
Visual dynamics: Probabilistic future frame synthesis via cross convolutional networks. In Advances in Neural Information Processing Systems
Tianfan Xue, Jiajun Wu, Katherine Bouman, and Bill Freeman. 2016 · 2016
Later among the works it cites.
Attribute2image: Conditional image generation from visual attributes. In European Conference on Computer Vision
Xinchen Yan, Jimei Yang, Kihyuk Sohn, and Honglak Lee. 2016 · 2016
Later among the works it cites.
View synthesis by appearance flow. In European Conference on Computer Vision
Tinghui Zhou, Shubham Tulsiani, Weilun Sun, Jitendra Malik, and Alexei A Efros. 2016 · 2016
Later among the works it cites.
Martin Arjovsky, Soumith Chintala, and Léon Bottou. 2017 · 2017
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Video Frame Synthesis using Deep Voxel Flow
Ziwei Liu, Raymond Yeh, Xiaoou Tang, Yiming Liu, and Aseem Agarwala. 2017 · 2017
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Transformation-based models of video sequences
Joost van Amersfoort, Anitha Kannan, Marc’Aurelio Ranzato, Arthur Szlam, Du Tran, and Soumith Chintala. 2017 · 2017
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Spatial transformer networks. In Advances in Neural Information Processing Systems
Max Jaderberg, Karen Simonyan, Andrew Zisserman, and others. 2015 · 2025
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