356 citations · 387 across the 20 of their papers we have counts for
5 papers · 1 filter
EnhanceNet: Single Image Super-Resolution Through Automated Texture Synthesis
Mehdi S. M. Sajjadi, Bernhard Schölkopf, Michael Hirsch
Single image super-resolution is the task of inferring a high-resolution image from a single low-resolution input. Traditionally, the performance of algorithms for this task is mea…
Depth Estimation Through a Generative Model of Light Field Synthesis
Mehdi S. M. Sajjadi, Rolf Köhler, Bernhard Schölkopf +1
Light field photography captures rich structural information that may facilitate a number of traditional image processing and computer vision tasks. A crucial ingredient in such en…
Regularization With Stochastic Transformations and Perturbations for Deep Semi-Supervised Learning
Mehdi Sajjadi, Mehran Javanmardi, Tolga Tasdizen
Effective convolutional neural networks are trained on large sets of labeled data. However, creating large labeled datasets is a very costly and time-consuming task. Semi-supervise…
Mutual Exclusivity Loss for Semi-Supervised Deep Learning
Mehdi Sajjadi, Mehran Javanmardi, Tolga Tasdizen
In this paper we consider the problem of semi-supervised learning with deep Convolutional Neural Networks (ConvNets). Semi-supervised learning is motivated on the observation that…
Unsupervised Total Variation Loss for Semi-supervised Deep Learning of Semantic Segmentation
Mehran Javanmardi, Mehdi Sajjadi, Ting Liu +1
We introduce a novel unsupervised loss function for learning semantic segmentation with deep convolutional neural nets (ConvNet) when densely labeled training images are not availa…