most citedImageBART: Bidirectional Context with Multinomial Diffusion for Autoregressive Image Synthesis

52 citations · 52 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV202152 cited

ImageBART: Bidirectional Context with Multinomial Diffusion for Autoregressive Image Synthesis

Patrick Esser, Robin Rombach, Andreas Blattmann +1

Autoregressive models and their sequential factorization of the data likelihood have recently demonstrated great potential for image representation and synthesis. Nevertheless, the…

cs.CV2021

iPOKE: Poking a Still Image for Controlled Stochastic Video Synthesis

Andreas Blattmann, Timo Milbich, Michael Dorkenwald +1

How would a static scene react to a local poke? What are the effects on other parts of an object if you could locally push it? There will be distinctive movement, despite evident v…

cs.CV2021

Understanding Object Dynamics for Interactive Image-to-Video Synthesis

Andreas Blattmann, Timo Milbich, Michael Dorkenwald +1

What would be the effect of locally poking a static scene? We present an approach that learns naturally-looking global articulations caused by a local manipulation at a pixel level…

cs.CV2021

Stochastic Image-to-Video Synthesis using cINNs

Michael Dorkenwald, Timo Milbich, Andreas Blattmann +3

Video understanding calls for a model to learn the characteristic interplay between static scene content and its dynamics: Given an image, the model must be able to predict a futur…

cs.CV2021

Behavior-Driven Synthesis of Human Dynamics

Andreas Blattmann, Timo Milbich, Michael Dorkenwald +1

Generating and representing human behavior are of major importance for various computer vision applications. Commonly, human video synthesis represents behavior as sequences of pos…