67 citations · 182 across the 17 of their papers we have counts for
8 papers · 1 filter
Learning to Take Directions One Step at a Time
Qiyang Hu, Adrian Wälchli, Tiziano Portenier +2
We present a method to generate a video sequence given a single image. Because items in an image can be animated in arbitrarily many different ways, we introduce as control signal…
Unsupervised 3D Shape Learning from Image Collections in the Wild
Attila Szabó, Paolo Favaro
We present a method to learn the 3D surface of objects directly from a collection of images. Previous work achieved this capability by exploiting additional manual annotation, such…
Deep Bilevel Learning
Simon Jenni, Paolo Favaro
We present a novel regularization approach to train neural networks that enjoys better generalization and test error than standard stochastic gradient descent. Our approach is base…
Self-Supervised Feature Learning by Learning to Spot Artifacts
Simon Jenni, Paolo Favaro
We introduce a novel self-supervised learning method based on adversarial training. Our objective is to train a discriminator network to distinguish real images from images with sy…
Boosting Self-Supervised Learning via Knowledge Transfer
Mehdi Noroozi, Ananth Vinjimoor, Paolo Favaro +1
In self-supervised learning, one trains a model to solve a so-called pretext task on a dataset without the need for human annotation. The main objective, however, is to transfer th…
Learning to Extract a Video Sequence from a Single Motion-Blurred Image
Meiguang Jin, Givi Meishvili, Paolo Favaro
We present a method to extract a video sequence from a single motion-blurred image. Motion-blurred images are the result of an averaging process, where instant frames are accumulat…