A classical problem in computer vision is to infer a 3D scene representa...
Time series forecasting is often fundamental to scientific and engineeri...
Cutting and pasting image segments feels intuitive: the choice of source...
We present a generative model that is defined on finite sets of exchange...
Visualizing an outfit is an essential part of shopping for clothes. Due ...
We introduce a hierarchical Bayesian approach to tackle the challenging
...
Personalized size and fit recommendations bear crucial significance for ...
Deep Reinforcement Learning has been shown to be very successful in comp...
Parametric generative deep models are state-of-the-art for photo and
non...
In this paper, we propose a method that disentangles the effects of mult...
GANs excel at learning high dimensional distributions, but they can upda...
This work explores maximum likelihood optimization of neural networks th...
This paper presents a novel framework for generating texture mosaics wit...
We present a novel method to solve image analogy problems : it allows to...
This paper introduces a novel approach to texture synthesis based on
gen...
Generative adversarial networks (GANs) are a recent approach to train
ge...