313 citations · 337 across the 3 of their papers we have counts for
5 papers
ComboGAN: Unrestrained Scalability for Image Domain Translation
Asha Anoosheh, Eirikur Agustsson, Radu Timofte +1
This year alone has seen unprecedented leaps in the area of learning-based image translation, namely CycleGAN, by Zhu et al. But experiments so far have been tailored to merely two…
Optimal transport maps for distribution preserving operations on latent spaces of Generative Models
Eirikur Agustsson, Alexander Sage, Radu Timofte +1
Generative models such as Variational Auto Encoders (VAEs) and Generative Adversarial Networks (GANs) are typically trained for a fixed prior distribution in the latent space, such…
WebVision Database: Visual Learning and Understanding from Web Data
Wen Li, Limin Wang, Wei Li +2
In this paper, we present a study on learning visual recognition models from large scale noisy web data. We build a new database called WebVision, which contains more than mi…
WebVision Challenge: Visual Learning and Understanding With Web Data
Wen Li, Limin Wang, Wei Li +5
We present the 2017 WebVision Challenge, a public image recognition challenge designed for deep learning based on web images without instance-level human annotation. Following the…
k2-means for fast and accurate large scale clustering
Eirikur Agustsson, Radu Timofte, Luc Van Gool
We propose k^2-means, a new clustering method which efficiently copes with large numbers of clusters and achieves low energy solutions. k^2-means builds upon the standard k-means (…