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We present Pyramid Attention Broadcast (PAB), a real-time, high quality and training-free approach for DiT-based video generation.
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Generative adversarial nets
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U-net: Convolutional networks for biomedical image segmentation
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Neural discrete representation learning
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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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Moonshine: Distilling with cheap convolutions
Elliot J Crowley, Gavin Gray, and Amos J Storkey · 2018
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The unreasonable effectiveness of deep features as a perceptual metric
Richard Zhang, Phillip Isola, Alexei A Efros, Eli Shechtman, and Oliver Wang · 2018
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Post training 4-bit quantization of convolutional networks for rapid-deployment
Ron Banner, Yury Nahshan, and Daniel Soudry · 2019
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Denoising Diffusion Probabilistic Models, 2020
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Latent Video Transformer, 2020
Ruslan Rakhimov, Denis Volkhonskiy, Alexey Artemov, Denis Zorin, and Evgeny Burnaev · 2020
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Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2020
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Frozen in time: A joint video and image encoder for end-to-end retrieval
Max Bain, Arsha Nagrani, Gül Varol, and Andrew Zisserman · 2021
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Gotta Go Fast When Generating Data with Score-Based Models, 2021
Alexia Jolicoeur-Martineau, Ke Li, Rémi Piché-Taillefer, Tal Kachman, and Ioannis Mitliagkas · 2021
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Score-Based Generative Modeling through Stochastic Differential Equations, 2021
Yang Song, Jascha Sohl-Dickstein, Diederik P. Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole · 2021
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Predicting attention sparsity in transformers
Marcos Treviso, António Góis, Patrick Fernandes, Erick Fonseca, and André FT Martins · 2021
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Tri Dao, Dan Fu, Stefano Ermon, Atri Rudra, and Christopher Ré · 2022
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Flexible Diffusion Modeling of Long Videos, 2022
William Harvey, Saeid Naderiparizi, Vaden Masrani, Christian Weilbach, and Frank Wood · 2022
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Elucidating the Design Space of Diffusion-Based Generative Models, 2022
Tero Karras, Miika Aittala, Timo Aila, and Samuli Laine · 2022
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Cheng Lu, Yuhao Zhou, Fan Bao, Jianfei Chen, Chongxuan Li, and Jun Zhu · 2022
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Llm-pruner: On the structural pruning of large language models
Xinyin Ma, Gongfan Fang, and Xinchao Wang · 2023
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Imran Othman · 2023
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Scalable diffusion models with transformers
William Peebles and Saining Xie · 2023
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Adversarial diffusion distillation
Axel Sauer, Dominik Lorenz, Andreas Blattmann, and Robin Rombach · 2023
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Yuzhang Shang, Zhihang Yuan, Bin Xie, Bingzhe Wu, and Yan Yan · 2023
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ControlVideo: Training-free Controllable Text-to-Video Generation, 2023
Yabo Zhang, Yuxiang Wei, Dongsheng Jiang, Xiaopeng Zhang, Wangmeng Zuo, and Qi Tian · 2023
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Tim Salimans and Jonathan Ho · 2022
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Make-A-Video: Text-to-Video Generation without Text-Video Data, 2022
Uriel Singer, Adam Polyak, Thomas Hayes, Xi Yin, Jie An, Songyang Zhang, Qiyuan Hu, Harry Yang, Oron Ashual, Oran Gafni, Devi Parikh, Sonal Gupta, and Yaniv Taigman · 2022
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