230 citations · 493 across the 3 of their papers we have counts for
4 papers
The Unreasonable Effectiveness of Linear Prediction as a Perceptual Metric
Daniel Severo, Lucas Theis, Johannes Ballé
We show how perceptual embeddings of the visual system can be constructed at inference-time with no training data or deep neural network features. Our perceptual embeddings are sol…
Amortised MAP Inference for Image Super-resolution
Casper Kaae Sønderby, Jose Caballero, Lucas Theis +2
Image super-resolution (SR) is an underdetermined inverse problem, where a large number of plausible high-resolution images can explain the same downsampled image. Most current sin…
Is the deconvolution layer the same as a convolutional layer?
Wenzhe Shi, Jose Caballero, Lucas Theis +4
In this note, we want to focus on aspects related to two questions most people asked us at CVPR about the network we presented. Firstly, What is the relationship between our propos…
Deep Gaze I: Boosting Saliency Prediction with Feature Maps Trained on ImageNet
Matthias Kümmerer, Lucas Theis, Matthias Bethge
Recent results suggest that state-of-the-art saliency models perform far from optimal in predicting fixations. This lack in performance has been attributed to an inability to model…