4 citations · 4 across the 2 of their papers we have counts for
6 papers
Separator-Transducer-Segmenter: Streaming Recognition and Segmentation of Multi-party Speech
Ilya Sklyar, Anna Piunova, Christian Osendorfer
Streaming recognition and segmentation of multi-party conversations with overlapping speech is crucial for the next generation of voice assistant applications. In this work we addr…
No Representation without Transformation
Giorgio Giannone, Saeed Saremi, Jonathan Masci +1
We extend the framework of variational autoencoders to represent transformations explicitly in the latent space. In the family of hierarchical graphical models that emerges, the la…
Recurrent Neural Processes
Timon Willi, Jonathan Masci, Jürgen Schmidhuber +1
We extend Neural Processes (NPs) to sequential data through Recurrent NPs or RNPs, a family of conditional state space models. RNPs model the state space with Neural Processes. Giv…
Two-Stage Peer-Regularized Feature Recombination for Arbitrary Image Style Transfer
Jan Svoboda, Asha Anoosheh, Christian Osendorfer +1
This paper introduces a neural style transfer model to generate a stylized image conditioning on a set of examples describing the desired style. The proposed solution produces high…
Deep Iterative Surface Normal Estimation
Jan Eric Lenssen, Christian Osendorfer, Jonathan Masci
This paper presents an end-to-end differentiable algorithm for robust and detail-preserving surface normal estimation on unstructured point-clouds. We utilize graph neural networks…
Unsupervised Feature Learning for low-level Local Image Descriptors
Christian Osendorfer, Justin Bayer, Sebastian Urban +1
Unsupervised feature learning has shown impressive results for a wide range of input modalities, in particular for object classification tasks in computer vision. Using a large amo…