Max Reimann

Max Reimann
Hasso Plattner Institute · Research Group Computer Graphics Systems

Master of Science

About

17
Publications
2,679
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15
Citations

Publications

Publications (17)
Article
Full-text available
Fast style transfer methods have recently gained popularity in art-related applications as they make a generalized real-time stylization of images practicable. However, they are mostly limited to one-shot stylizations concerning the interactive adjustment of style elements. In particular, the expressive control over stroke sizes or stroke orientati...
Preprint
Full-text available
Image acquisition in low-light conditions suffers from poor quality and significant degradation in visual aesthetics. This affects the visual perception of the acquired image and the performance of various computer vision and image processing algorithms applied after acquisition. Especially for videos, the additional temporal domain makes it more c...
Presentation
Full-text available
Presentation of research paper "Interactive Multi-level Stroke Control for Neural Style Transfer" at Cyberworlds 2021
Conference Paper
Full-text available
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. In contrast to current mobile neural style transfer apps, StyleTune supports users to adjust both the size and orientation of style elements, such as brushstrokes...
Conference Paper
Full-text available
We present StyleTune, a mobile app for interactive style transfer enhancement that enables global and spatial control over stroke elements and can generate high fidelity outputs. The app uses adjustable neural style transfer (NST) networks to enable art-direction of stroke size and orientation in the output image. The implemented approach enables c...
Preprint
Full-text available
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. In contrast to current mobile neural style transfer apps, StyleTune supports users to adjust both the size and orientation of style elements, such as brushstrokes...
Presentation
Full-text available
Presentation of research paper "Interactive Photo Editing on Smartphones via Intrinsic Decomposition" presented at 42nd Annual Conference of the European Association for Computer Graphics (Eurographics’2021).
Presentation
Full-text available
Presentation of education paper "Teaching Data-driven Video Processing via Crowdsourced Data Collection" presented at 42nd Annual Conference of the European Association for Computer Graphics (Eurographics’2021).
Conference Paper
Full-text available
This paper presents the concept and experience of teaching an undergraduate course on data-driven image and video processing. When designing visual effects that make use of Machine Learning (ML) models for image-based analysis or processing, the availability of training data typically represents a key limitation when it comes to feasibility and eff...
Article
Full-text available
Intrinsic decomposition refers to the problem of estimating scene characteristics, such as albedo and shading, when one view or multiple views of a scene are provided. The inverse problem setting, where multiple unknowns are solved given a single known pixel-value, is highly under-constrained. When provided with correlating image and depth data, in...
Article
Full-text available
Mobile expressive rendering gained increasing popularity among users seeking casual creativity by image stylization and supports the development of mobile artists as a new user group. In particular, neural style transfer has advanced as a core technology to emulate characteristics of manifold artistic styles. However, when it comes to creative expr...
Conference Paper
Full-text available
We present ViVid, a mobile app for iOS that empowers users to express dynamics in stylized Live Photos. This app uses state-of the-art computer-vision techniques based on convolutional neural networks to estimate motion in the video footage that is captured together with a photo. Based on this analysis and best practices of contemporary art, photos...
Conference Paper
Full-text available
Mobile expressive rendering gained increasing popularity amongst users seeking casual creativity by image stylization and supports the development of mobile artists as a new user group. In particular, the neural style transfer has advanced as a core technology to emulate characteristics of manifold artistic styles and media without deep prior knowl...
Poster
Full-text available
This work presents enhancements to state-of-the-art adaptive neural style transfer techniques, thereby providing a generalized user interface with creativity tool support for lower-level local control to facilitate the demanding interactive editing on mobile devices. The approaches are implemented in a mobile app that is designed for orchestration...
Conference Paper
Full-text available
We present MaeSTrO, a mobile app for image stylization that empowers users to direct, edit and perform a neural style transfer with creative control. The app uses iterative style transfer, multi-style generative and adaptive networks to compute and apply flexible yet comprehensive style models of arbitrary images at run-time. Compared to other mobi...
Book
Eine dezentrale Energieversorgung ist ein erster Schritt in Richtung Energiewende. Dabei werden auch in Mehrfamilienhäusern vermehrt verschiedene Strom- und Wärmeerzeuger eingesetzt. Besonders in Deutschland kommen in diesem Zusammenhang Blockheizkraftwerke immer häufiger zum Einsatz, weil sie Gas sehr effizient in Strom und Wärme umwandeln können....

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