A Generative Method for Textured Motion: Analysis and Synthesis

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Learning Energy-Based Spatial-Temporal Generative ConvNets for Dynamic Patterns (2019, background): “S.-C. Zhu and Y.N. Wu are with the Department of Statistics, University of California, Los Angeles, CA 90095 USA.”
Synthesizing Dynamic Patterns by Spatial-Temporal Generative ConvNet (2016, background): “Dynamic textures or textured motions have been studied by [2, 24, 25, 9].”
Learning Generator Networks for Dynamic Patterns (2019, background): “These approaches can be used for pattern synthesis [33, 5], and future generation in videos [19, 27, 37].”
Synthesising Dynamic Textures using Convolutional Neural Networks (2017, background): “[1, 2, 3, 4, 5, 6, 7]) and recently spatio-temporal Convolutional Neural Networks (CNNs) were proposed to generate samples of dynamic textures [8].”