VideoFusion: Decomposed Diffusion Models for High-Quality Video Generation

15 March 2023

Papers citing "VideoFusion: Decomposed Diffusion Models for High-Quality Video Generation"

8 / 58 papers shown

Title
Generative Modeling by Estimating Gradients of the Data Distribution Yang Song Stefano Ermon SyDa DiffM 216 3,893 0 12 Jul 2019
Train Sparsely, Generate Densely: Memory-efficient Unsupervised Training of High-resolution Temporal GAN Masaki Saito Shunta Saito Masanori Koyama Sosuke Kobayashi 71 147 0 22 Nov 2018
Neural Discrete Representation Learning Aaron van den Oord Oriol Vinyals Koray Kavukcuoglu BDL SSL OCL 215 5,004 0 02 Nov 2017
Learning to Generate Time-Lapse Videos Using Multi-Stage Dynamic Generative Adversarial Networks Wei Xiong Wenhan Luo Lin Ma Wen Liu Jiebo Luo GAN 51 181 0 22 Sep 2017
MoCoGAN: Decomposing Motion and Content for Video Generation Sergey Tulyakov Ming-Yuan Liu Xiaodong Yang Jan Kautz GAN 129 1,147 0 17 Jul 2017
Masked Autoregressive Flow for Density Estimation George Papamakarios Theo Pavlakou Iain Murray 204 1,351 0 19 May 2017
Generating Videos with Scene Dynamics Carl Vondrick Hamed Pirsiavash Antonio Torralba GAN VGen 180 1,468 0 08 Sep 2016
Deep Unsupervised Learning using Nonequilibrium Thermodynamics Jascha Narain Sohl-Dickstein Eric A. Weiss Niru Maheswaranathan Surya Ganguli SyDa DiffM 279 6,925 0 12 Mar 2015