… In this paper, we model a generative prior for image-space scene motion, ie, the motion
of all pixels in a single image. This model is trained on motion trajectories automatically …

… with this connection between dynamics and sampling, many large-scale generative
models … of generative models to spiking neurons 20,21 and turbulent flow time series 22 . …

… dynamics of density maps by generating interpolation information. First, a trained generative
… Third, for dynamic visualization of large-scale density maps, we extend this approach to …

… generative smoothness regularization on manifolds (SToRM) model for the recovery of dynamic
image … The model assumes that the images in the dataset are non-linear mappings of low…

… of dynamic appearance manifolds. In [27] we extended the framework to learn a … generative
model that separates appearance variations from the intrinsics underlying dynamics manifold …

… Specifically, we design (1) Dynamic Semantic Evolution (DSE) module, which first aggregates
historical image features to summarize the generative feedback, and then dynamically se…

… We introduce a novel generative smoothness regularization … dynamic image data from
highly undersampled measurements. The proposed generative framework represents the image …

… The proposed method introduces a dynamic memory module to refine fuzzy image contents,
… a dynamic memory component to generate high-quality images even if the initial image is …

… the scale of generated videos and neglects continuous dynamics. In this paper, we found
that the … dynamics-aware implicit generative adversarial network (DIGAN), a novel generative …

… work in the literature on synthesizing dynamic patterns based on the ConvNet… dynamic
patterns by generalizing the generative ConvNet model recently proposed by [29]. The generative …