Hyper-Realist Rendering: A Theoretical Framework
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Abstract (arXiv)
This is the first paper in a series on hyper-realist rendering. In this paper, we introduce the concept of hyper-realist rendering and present a theoretical framework to obtain hyper-realist images. We are using the term Hyper-realism as an umbrella word that captures all types of visual artifacts that can evoke an impression of reality. The hyper-realist artifacts are visual representations that are not necessarily created by following logical and physical principles and can still be perceived as representations of reality. This idea stems from the principles of representational arts, which attain visually acceptable renderings of scenes without implementing strict physical laws of optics and materials. The objective of this work is to demonstrate that it is possible to obtain visually acceptable illusions of reality by employing such artistic approaches. With representational art methods, we can even obtain an alternate illusion of reality that looks more real even when it is not real. This paper demonstrates that it is common to create illusions of reality in visual arts with examples of paintings by representational artists. We propose an approach to obtain expressive local and global illuminations to obtain these stylistic illusions with a set of well-defined and formal methods.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 23 Jan 2024.
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Citing papers per year: 2024: 4; 2025: 0; 2026: 1.
5 papers.
- 2024GenPluSSS: A Genetic Algorithm Based Plugin for Measured Subsurface Scattering Representationcited by 4
- 2024MelNet: A Real-Time Deep Learning Algorithm for Object Detectioncited by 3
- 2024ExTTNet: A Deep Learning Algorithm for Extracting Table Texts from Invoice Imagescited by 2
- 2024LightFFDNets: Lightweight Convolutional Neural Networks for Rapid Facial Forgery Detectioncited by 1
- 2026OkanNet: A Lightweight Deep Learning Architecture for Classification of Brain Tumor from MRI Imagescited by 0
- 2026OkanNet: A Lightweight Deep Learning Architecture for Classification of Brain Tumor from MRI Images1 Apr 2026
- 2024LightFFDNets: Lightweight Convolutional Neural Networks for Rapid Facial Forgery Detection18 Nov 2024
- 2024ExTTNet: A Deep Learning Algorithm for Extracting Table Texts from Invoice Images3 Feb 2024
- 2024MelNet: A Real-Time Deep Learning Algorithm for Object Detection31 Jan 2024
- 2024GenPluSSS: A Genetic Algorithm Based Plugin for Measured Subsurface Scattering Representation26 Jan 2024