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Given the remarkable achievements in image generation through diffusion models, the research community has shown increasing interest in extending these models to video generation.
Framewise phoneme classification with bidirectional lstm and other neural network architectures
Alex Graves and Jürgen Schmidhuber · 2005
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Score-based generative modeling through stochastic differential equations
Yang Song, Jascha Sohl-Dickstein, Diederik P Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole · 2011
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Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2013
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Empirical evaluation of gated recurrent neural networks on sequence modeling
Junyoung Chung, Caglar Gulcehre, KyungHyun Cho, and Yoshua Bengio · 2014
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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
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Deep unsupervised learning using nonequilibrium thermodynamics
Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015
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J. L. Ba, J. R. Kiros, and G. E. Hinton · 2016
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Deep residual learning for image recognition
Kaiming He et al · 2016
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Generating videos with scene dynamics
C. Vondrick, H. Pirsiavash, and A. Torralba · 2016
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Quo vadis, action recognition? a new model and the kinetics dataset
J. Carreira and A. Zisserman · 2017
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Carla: An open urban driving simulator
Alexey Dosovitskiy, German Ros, Felipe Codevilla, Antonio Lopez, and Vladlen Koltun · 2017
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Temporal generative adversarial nets with singular value clipping
M. Saito, E. Matsumoto, and S. Saito · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Sigmoid-weighted linear units for neural network function approximation in reinforcement learning
Stefan Elfwing, Eiji Uchibe, and Kenji Doya · 2018
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Neural scene representation and rendering
SM Ali Eslami et al · 2018
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Temporal difference variational auto-encoder
K. Gregor and F. Besse · 2018
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Efficient attention: Attention with linear complexities
Zhuoran Shen, Mingyuan Zhang, Haiyu Zhao, Shuai Yi, and Hongsheng Li · 2018
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Mocogan: Decomposing motion and content for video generation
Sergey Tulyakov, Ming-Yu Liu, Xiaodong Yang, and Jan Kautz · 2018
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Towards accurate generative models of video: A new metric challenges
Thomas Unterthiner, Sjoerd van Steenkiste, Karol Kurach, Raphael Marinier, Marcin Michalski, and Sylvain Gelly · 2018
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Minerl: A large-scale dataset of minecraft demonstrations
William H Guss, Brandon Houghton, Nicholay Topin, Phillip Wang, Cayden Codel, Manuela Veloso, and Ruslan Salakhutdinov · 2019
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Variational temporal abstraction
T. Kim, S. Ahn, and Y. Bengio · 2019
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An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al · 2020
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Hippo: Recurrent memory with optimal polynomial projections
Albert Gu, Tri Dao, Stefano Ermon, Atri Rudra, and Christopher Ré · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
Cited alongside, same era.
Reformer: The efficient transformer
Nikita Kitaev, Lukasz Kaiser, and Anselm Levskaya · 2020
Cited alongside, same era.
Linformer: Self-attention with linear complexity, 2020
Sinong Wang, Belinda Z. Li, Madian Khabsa, Han Fang, and Hao Ma · 2020
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Diffusion models beat gans on image synthesis
Prafulla Dhariwal and Alex Nichol · 2021
Cited alongside, same era.
Efficiently modeling long sequences with structured state spaces
Albert Gu, Karan Goel, and Christopher Ré · 2021
Cited alongside, same era.
Mcvd-masked conditional video diffusion for prediction, generation, and interpolation
Vikram Voleti, Alexia Jolicoeur-Martineau, and Chris Pal · 2022
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Junxiong Wang, Jing Nathan Yan, Albert Gu, and Alexander M Rush · 2022
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Magicvideo: Efficient video generation with latent diffusion models
Daquan Zhou et al · 2022
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Decision s4: Efficient sequence-based rl via state spaces layers
Shmuel Bar David, Itamar Zimerman, Eliya Nachmani, and Lior Wolf · 2023
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Align your latents: High-resolution video synthesis with latent diffusion models
Andreas Blattmann, Robin Rombach, Huan Ling, Tim Dockhorn, Seung Wook Kim, Sanja Fidler, and Karsten Kreis · 2023
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Diederik P Kingma, Tim Salimans, Ben Poole, and Jonathan Ho · 2021
Cited alongside, same era.
Improved denoising diffusion probabilistic models
Alexander Quinn Nichol and Prafulla Dhariwal · 2021
Cited alongside, same era.
Clockwork variational autoencoders
Vaibhav Saxena, Jimmy Ba, and Danijar Hafner · 2021
Cited alongside, same era.
Long range arena: A benchmark for efficient transformers
Yi Tay, Mostafa Dehghani, Samira Abnar, Yikang Shen, Dara Bahri, Philip Pham, Jinfeng Rao, Liu Yang, Sebastian Ruder, and Donald Metzler · 2021
Cited alongside, same era.
Videogpt: Video generation using vq-vae and transformers
Wilson Yan et al · 2021
Cited alongside, same era.
Long video generation with time-agnostic vqgan and time-sensitive transformer
Songwei Ge, Thomas Hayes, Harry Yang, Xi Yin, Guan Pang, David Jacobs, Jia-Bin Huang, and Devi Parikh · 2022
Cited alongside, same era.
It’s raw! audio generation with state-space models
Karan Goel, Albert Gu, Chris Donahue, and Christopher Ré · 2022
Cited alongside, same era.
“hungry hungry hippos: Towards language modeling with state space models”
Tri Dao, Daniel Y Fu, Khaled K Saab, Armin W Thomas, Atri Rudra, and Christopher Ré · 2023
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Facing off world model backbones: Rnns, transformers, and s4
Fei Deng, Junyeong Park, and Sungjin Ahn · 2023
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Mamba: Linear-time sequence modeling with selective state spaces
Albert Gu and Tri Dao · 2023
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Modelling long range dependencies in nd: From task-specific to a general purpose cnn
David M Knigge, David W Romero, Albert Gu, Efstratios Gavves, Erik J Bekkers, Jakub Mikolaj Tomczak, Mark Hoogendoorn, and Jan-jakob Sonke · 2023
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Structured state space models for in-context reinforcement learning
Chris Lu, Yannick Schroecker, Albert Gu, Emilio Parisotto, Jakob Foerster, Satinder Singh, and Feryal Behbahani · 2023
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Long range language modeling via gated state spaces
Harsh Mehta, Ankit Gupta, Ashok Cutkosky, and Behnam Neyshabur · 2023
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Simplified state space layers for sequence modeling
Jimmy T.H. Smith, Andrew Warrington, and Scott Linderman · 2023
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Selective structured state-spaces for long-form video understanding
Jue Wang, Wentao Zhu, Pichao Wang, Xiang Yu, Linda Liu, Mohamed Omar, and Raffay Hamid · 2023
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Diffusion models without attention
Jing Nathan Yan, Jiatao Gu, and Alexander M Rush · 2023
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Nuwa-xl: Diffusion over diffusion for extremely long video generation
Shengming Yin et al · 2023
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Deep latent state space models for time-series generation
Linqi Zhou, Michael Poli, Winnie Xu, Stefano Massaroli, and Stefano Ermon · 2023
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Lamamba-diff: Linear-time high-fidelity diffusion models based on local attention and mamba
Yunxiang Fu, Chaoqi Chen, and Yizhou Yu · 2024
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Matten: Video generation with mamba-attention
Yu Gao et al · 2024
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Zigma: Zigzag mamba diffusion model
Vincent Tao Hu et al · 2024
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Videomamba: State space model for efficient video understanding
Kunchang Li et al · 2024
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Vmamba: Visual state space model
Y. Liu, Y. Tian, Y. Zhao, H. Yu, L. Xie, Y. Wang, Q. Ye, and Y. Liu · 2024
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U-mamba: Enhancing long-range dependency for biomedical image segmentation
Jun Ma, Feifei Li, and Bo Wang · 2024
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Vision mamba: Efficient visual representation learning with bidirectional state space model
Lianghui Zhu et al · 2024
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