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Generating temporally coherent high fidelity video is an important milestone in generative modeling research.
A connection between score matching and denoising autoencoders
Pascal Vincent · 2011
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A dataset of 101 human actions classes from videos in the wild
Khurram Soomro, Amir Roshan Zamir, and Mubarak Shah · 2012
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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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Learning spatiotemporal features with 3d convolutional networks
Du Tran, Lubomir Bourdev, Rob Fergus, Lorenzo Torresani, and Manohar Paluri · 2015
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3d u-net: learning dense volumetric segmentation from sparse annotation
Özgün Çiçek, Ahmed Abdulkadir, Soeren S Lienkamp, Thomas Brox, and Olaf Ronneberger · 2016
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Improved techniques for training gans
Tim Salimans, Ian Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, and Xi Chen · 2016
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Sergey Zagoruyko and Nikos Komodakis · 2016
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Stochastic variational video prediction
Mohammad Babaeizadeh, Chelsea Finn, Dumitru Erhan, Roy H Campbell, and Sergey Levine · 2017
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Quo vadis, action recognition? a new model and the kinetics dataset
Joao Carreira and Andrew Zisserman · 2017
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Self-supervised visual planning with temporal skip connections
Frederik Ebert, Chelsea Finn, Alex X Lee, and Sergey Levine · 2017
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GANs trained by a two time-scale update rule converge to a local Nash equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017
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The kinetics human action video dataset
Will Kay, Joao Carreira, Karen Simonyan, Brian Zhang, Chloe Hillier, Sudheendra Vijayanarasimhan, Fabio Viola, Tim Green, Trevor Back, Paul Natsev, et al · 2017
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PixelCNN++: Improving the PixelCNN with discretized logistic mixture likelihood and other modifications
Tim Salimans, Andrej Karpathy, Xi Chen, and Diederik P Kingma · 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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Gender shades: Intersectional accuracy disparities in commercial gender classification
Joy Buolamwini and Timnit Gebru · 2018
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Women also snowboard: Overcoming bias in captioning models
Kaylee Burns, Lisa Hendricks, Trevor Darrell, and Anna Rohrbach · 2018
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A short note about kinetics-600
Joao Carreira, Eric Noland, Andras Banki-Horvath, Chloe Hillier, and Andrew Zisserman · 2018
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PixelSNAIL: An improved autoregressive generative model
Xi Chen, Nikhil Mishra, Mostafa Rohaninejad, and Pieter Abbeel · 2018
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Stochastic adversarial video prediction
Alex X Lee, Richard Zhang, Frederik Ebert, Pieter Abbeel, Chelsea Finn, and Sergey Levine · 2018
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Self-attention with relative position representations
Peter Shaw, Jakob Uszkoreit, and Ashish Vaswani · 2018
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Mocogan: Decomposing motion and content for video generation
Sergey Tulyakov, Ming-Yu Liu, Xiaodong Yang, and Jan Kautz · 2018
Cited alongside, same era.
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
Cited alongside, same era.
Non-local neural networks
Xiaolong Wang, Ross Girshick, Abhinav Gupta, and Kaiming He · 2018
Cited alongside, same era.
Adversarial video generation on complex datasets
Aidan Clark, Jeff Donahue, and Karen Simonyan · 2019
Cited alongside, same era.
BERT: pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2019
Cited alongside, same era.
Diffusion models beat GANs on image synthesis
Prafulla Dhariwal and Alexander Nichol · 2021
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Latent neural differential equations for video generation
Cade Gordon and Natalie Parde · 2021
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Classifier-free diffusion guidance
Jonathan Ho and Tim Salimans · 2021
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Cascaded diffusion models for high fidelity image generation
Jonathan Ho, Chitwan Saharia, William Chan, David J Fleet, Mohammad Norouzi, and Tim Salimans · 2021
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Stochastic solutions for linear inverse problems using the prior implicit in a denoiser
Zahra Kadkhodaie and Eero Simoncelli · 2021
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Jonathan Ho, Nal Kalchbrenner, Dirk Weissenborn, and Tim Salimans · 2019
Cited alongside, same era.
VideoFlow: A flow-based generative model for video
Manoj Kumar, Mohammad Babaeizadeh, Dumitru Erhan, Chelsea Finn, Sergey Levine, Laurent Dinh, and Durk Kingma · 2019
Cited alongside, same era.
Generating high fidelity images with subscale pixel networks and multidimensional upscaling
Jacob Menick and Nal Kalchbrenner · 2019
Cited alongside, same era.
Generative modeling by estimating gradients of the data distribution
Yang Song and Stefano Ermon · 2019
Cited alongside, same era.
Neural stochastic differential equations: Deep latent gaussian models in the diffusion limit
Belinda Tzen and Maxim Raginsky · 2019
Cited alongside, same era.
Scaling autoregressive video models
Dirk Weissenborn, Oscar Täckström, and Jakob Uszkoreit · 2019
Cited alongside, same era.
Markov decision process for video generation
Vladyslav Yushchenko, Nikita Araslanov, and Stefan Roth · 2019
Cited alongside, same era.
Diederik P Kingma, Tim Salimans, Ben Poole, and Jonathan Ho · 2021
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DiffWave: A versatile diffusion model for audio synthesis
Zhifeng Kong, Wei Ping, Jiaji Huang, Kexin Zhao, and Bryan Catanzaro · 2021
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Ccvs: Context-aware controllable video synthesis
Guillaume Le Moing, Jean Ponce, and Cordelia Schmid · 2021
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Glide: Towards photorealistic image generation and editing with text-guided diffusion models
Alex Nichol, Prafulla Dhariwal, Aditya Ramesh, Pranav Shyam, Pamela Mishkin, Bob McGrew, Ilya Sutskever, and Mark Chen · 2021
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Improved denoising diffusion probabilistic models
Alexander Quinn Nichol and Prafulla Dhariwal · 2021
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Progressive distillation for fast sampling of diffusion models
Tim Salimans and Jonathan Ho · 2021
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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 · 2021
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Image representations learned with unsupervised pre-training contain human-like biases
Ryan Steed and Aylin Caliskan · 2021
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Jacob Walker, Ali Razavi, and Aäron van den Oord · 2021
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Deblurring via stochastic refinement
Jay Whang, Mauricio Delbracio, Hossein Talebi, Chitwan Saharia, Alexandros G Dimakis, and Peyman Milanfar · 2021
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NÜWA: Visual synthesis pre-training for neural visual world creation
Chenfei Wu, Jian Liang, Lei Ji, Fan Yang, Yuejian Fang, Daxin Jiang, and Nan Duan · 2021
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Videogpt: Video generation using vq-vae and transformers
Wilson Yan, Yunzhi Zhang, Pieter Abbeel, and Aravind Srinivas · 2021
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https://www.tensorflow.org/datasets , 2022
TensorFlow Datasets, a collection of ready-to-use datasets · 2022
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Dall-eval: Probing the reasoning skills and social biases of text-to-image generative transformers
Jaemin Cho, Abhay Zala, and Mohit Bansal · 2022
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Transframer: Arbitrary frame prediction with generative models
Charlie Nash, João Carreira, Jacob Walker, Iain Barr, Andrew Jaegle, Mateusz Malinowski, and Peter Battaglia · 2022
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Diffusion probabilistic modeling for video generation
Ruihan Yang, Prakhar Srivastava, and Stephan Mandt · 2022
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