Search Results for author: Matthias Trapp

Found 7 papers, 5 papers with code

Large-Scale Evaluation of Topic Models and Dimensionality Reduction Methods for 2D Text Spatialization

1 code implementation17 Jul 2023 Daniel Atzberger, Tim Cech, Willy Scheibel, Matthias Trapp, Rico Richter, Jürgen Döllner, Tobias Schreck

Together with a subsequent dimensionality reduction algorithm, topic models can be used for deriving spatializations for text corpora as two-dimensional scatter plots, reflecting semantic similarity between the documents and supporting corpus analysis.

Dimensionality Reduction Semantic Similarity +2

Interactive Control over Temporal Consistency while Stylizing Video Streams

1 code implementation2 Jan 2023 Sumit Shekhar, Max Reimann, Moritz Hilscher, Amir Semmo, Jürgen Döllner, Matthias Trapp

For stylization tasks, however, consistency control is an essential requirement as a certain amount of flickering adds to the artistic look and feel.

Image Stylization Video Stabilization +1

Controlling strokes in fast neural style transfer using content transforms

1 code implementation The Visual Computer 2022 Max Reimann, Benito Buchheim, Amir Semmo, Jürgen Döllner, Matthias Trapp

To demonstrate the real-world applicability of our approach, we present StyleTune, a mobile app for interactive editing of neural style transfers at multiple levels of control.

Style Transfer

Low-light Image and Video Enhancement via Selective Manipulation of Chromaticity

no code implementations9 Mar 2022 Sumit Shekhar, Max Reimann, Amir Semmo, Sebastian Pasewaldt, Jürgen Döllner, Matthias Trapp

For videos captured in the wild, we perform a user study to demonstrate the preference for our method in comparison to state-of-the-art approaches.

Video Enhancement

Interactive Multi-level Stroke Control for Neural Style Transfer

no code implementations25 Jun 2021 Max Reimann, Benito Buchheim, Amir Semmo, Jürgen Döllner, Matthias Trapp

We present StyleTune, a mobile app for interactive multi-level control of neural style transfers that facilitates creative adjustments of style elements and enables high output fidelity.

Style Transfer

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