Archiverse: an Approach for Immersive Cultural Heritage
- URL: http://arxiv.org/abs/2507.19376v1
- Date: Fri, 25 Jul 2025 15:26:18 GMT
- Title: Archiverse: an Approach for Immersive Cultural Heritage
- Authors: Wieslaw Kopeć, Anna Jaskulska, Władysław Fuchs, Wiktor Stawski, Stanisław Knapiński, Barbara Karpowicz, Rafał Masłyk,
- Abstract summary: Digital technologies and tools have transformed the way we can study cultural heritage.<n>Mixed Reality solutions have enabled researchers to examine cultural objects and artifacts more precisely and from new perspectives.<n>Virtual Reality (VR) and eXtended Reality (XR) can serve as tools to recreate and visualize the remains of historical cultural heritage.
- Score: 1.7919147309612766
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Digital technologies and tools have transformed the way we can study cultural heritage and the way we can recreate it digitally. Techniques such as laser scanning, photogrammetry, and a variety of Mixed Reality solutions have enabled researchers to examine cultural objects and artifacts more precisely and from new perspectives. In this part of the panel, we explore how Virtual Reality (VR) and eXtended Reality (XR) can serve as tools to recreate and visualize the remains of historical cultural heritage and experience it in simulations of its original complexity, which means immersive and interactive. Visualization of material culture exemplified by archaeological sites and architecture can be particularly useful when only ruins or archaeological remains survive. However, these advancements also bring significant challenges, especially in the area of transdisciplinary cooperation between specialists from many, often distant, fields, and the dissemination of virtual immersive environments among both professionals and the general public.
Related papers
- A Critical Assessment of Modern Generative Models' Ability to Replicate Artistic Styles [0.0]
This paper presents a critical assessment of the style replication capabilities of contemporary generative models.<n>We examine how effectively these models reproduce traditional artistic styles while maintaining structural integrity and compositional balance.<n>The analysis is based on a new large dataset of AI-generated works imitating artistic styles of the past.
arXiv Detail & Related papers (2025-02-21T07:00:06Z) - Time Travel: A Comprehensive Benchmark to Evaluate LMMs on Historical and Cultural Artifacts [65.90535970515266]
TimeTravel is a benchmark of 10,250 expert-verified samples spanning 266 distinct cultures across 10 major historical regions.<n>TimeTravel is designed for AI-driven analysis of manuscripts, artworks, inscriptions, and archaeological discoveries.<n>We evaluate contemporary AI models on TimeTravel, highlighting their strengths and identifying areas for improvement.
arXiv Detail & Related papers (2025-02-20T18:59:51Z) - Grand Challenges in Immersive Technologies for Cultural Heritage [6.678822458675665]
The integration of immersive technologies has transformed how cultural heritage is presented.<n>The adoption of these technologies also brings a range of challenges and potential risks.
arXiv Detail & Related papers (2024-12-03T21:39:01Z) - Diffusion-Based Visual Art Creation: A Survey and New Perspectives [51.522935314070416]
This survey explores the emerging realm of diffusion-based visual art creation, examining its development from both artistic and technical perspectives.
Our findings reveal how artistic requirements are transformed into technical challenges and highlight the design and application of diffusion-based methods within visual art creation.
We aim to shed light on the mechanisms through which AI systems emulate and possibly, enhance human capacities in artistic perception and creativity.
arXiv Detail & Related papers (2024-08-22T04:49:50Z) - Recent Trends in 3D Reconstruction of General Non-Rigid Scenes [104.07781871008186]
Reconstructing models of the real world, including 3D geometry, appearance, and motion of real scenes, is essential for computer graphics and computer vision.
It enables the synthesizing of photorealistic novel views, useful for the movie industry and AR/VR applications.
This state-of-the-art report (STAR) offers the reader a comprehensive summary of state-of-the-art techniques with monocular and multi-view inputs.
arXiv Detail & Related papers (2024-03-22T09:46:11Z) - Diffusion Based Augmentation for Captioning and Retrieval in Cultural
Heritage [28.301944852273746]
This paper introduces a novel approach to address the challenges of limited annotated data and domain shifts in the cultural heritage domain.
By leveraging generative vision-language models, we augment art datasets by generating diverse variations of artworks conditioned on their captions.
arXiv Detail & Related papers (2023-08-14T13:59:04Z) - ArK: Augmented Reality with Knowledge Interactive Emergent Ability [115.72679420999535]
We develop an infinite agent that learns to transfer knowledge memory from general foundation models to novel domains.
The heart of our approach is an emerging mechanism, dubbed Augmented Reality with Knowledge Inference Interaction (ArK)
We show that our ArK approach, combined with large foundation models, significantly improves the quality of generated 2D/3D scenes.
arXiv Detail & Related papers (2023-05-01T17:57:01Z) - Populating the Digital Space for Cultural Heritage with Heritage Digital
Twins [0.0]
The present paper concerns the design of the semantic infrastructure of the digital space for cultural heritage.
The concept is based on the Digital Twin, i.e. the digital counterpart of cultural heritage assets all incorporating digital information to them.
arXiv Detail & Related papers (2022-05-26T07:49:27Z) - When Creators Meet the Metaverse: A Survey on Computational Arts [19.409136374448675]
This article conducts a comprehensive survey on computational arts, describing novel artworks in blended virtual-physical realities.
Several remarkable types of novel creations in the expanded horizons of metaverse cyberspace have been reflected.
We propose several research agendas: democratising computational arts, digital privacy, and safety for metaverse artists, ownership recognition for digital artworks, technological challenges, and so on.
arXiv Detail & Related papers (2021-11-26T13:24:37Z) - OpenRooms: An End-to-End Open Framework for Photorealistic Indoor Scene
Datasets [103.54691385842314]
We propose a novel framework for creating large-scale photorealistic datasets of indoor scenes.
Our goal is to make the dataset creation process widely accessible.
This enables important applications in inverse rendering, scene understanding and robotics.
arXiv Detail & Related papers (2020-07-25T06:48:47Z) - State of the Art on Neural Rendering [141.22760314536438]
We focus on approaches that combine classic computer graphics techniques with deep generative models to obtain controllable and photo-realistic outputs.
This report is focused on the many important use cases for the described algorithms such as novel view synthesis, semantic photo manipulation, facial and body reenactment, relighting, free-viewpoint video, and the creation of photo-realistic avatars for virtual and augmented reality telepresence.
arXiv Detail & Related papers (2020-04-08T04:36:31Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.