XRZoo: A Large-Scale and Versatile Dataset of Extended Reality (XR) Applications

• URL: http://arxiv.org/abs/2412.06759v2
• Date: Tue, 10 Dec 2024 18:54:11 GMT
• Title: XRZoo: A Large-Scale and Versatile Dataset of Extended Reality (XR) Applications
• Authors: Shuqing Li, Chenran Zhang, Cuiyun Gao, Michael R. Lyu,
• Abstract summary: XRZoo contains 12,528 free XR applications, spanning nine app stores, across all XR techniques (i.e., AR, MR, and VR) and use cases.<n>We aim to foster reproducible XR software engineering and security research, enable cross-disciplinary investigations, and also support the development of advanced XR systems.
• Score: 36.285311508797825
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The rapid advancement of Extended Reality (XR, encompassing AR, MR, and VR) and spatial computing technologies forms a foundational layer for the emerging Metaverse, enabling innovative applications across healthcare, education, manufacturing, and entertainment. However, research in this area is often limited by the lack of large, representative, and highquality application datasets that can support empirical studies and the development of new approaches benefiting XR software processes. In this paper, we introduce XRZoo, a comprehensive and curated dataset of XR applications designed to bridge this gap. XRZoo contains 12,528 free XR applications, spanning nine app stores, across all XR techniques (i.e., AR, MR, and VR) and use cases, with detailed metadata on key aspects such as application descriptions, application categories, release dates, user review numbers, and hardware specifications, etc. By making XRZoo publicly available, we aim to foster reproducible XR software engineering and security research, enable cross-disciplinary investigations, and also support the development of advanced XR systems by providing examples to developers. Our dataset serves as a valuable resource for researchers and practitioners interested in improving the scalability, usability, and effectiveness of XR applications. XRZoo will be released and actively maintained.

Related papers

• Recent Advances and Future Directions in Extended Reality (XR): Exploring AI-Powered Spatial Intelligence [0.0]
  Extended Reality (XR), encompassing Augmented Reality (AR), Virtual Reality (VR) and Mixed Reality (MR), is a transformative technology bridging the physical and virtual world. This review examines XR's evolution through foundational framework - hardware ranging from monitors to sensors and software ranging from visual tasks to user interface. For future directions, attention should be given to the integration of multi-modal AI and IoT-driven digital twins to enable adaptive XR systems.
  arXiv  Detail & Related papers  (2025-04-22T15:11:55Z)
• Crossing the Reward Bridge: Expanding RL with Verifiable Rewards Across Diverse Domains [92.36624674516553]
  Reinforcement learning with verifiable rewards (RLVR) has demonstrated significant success in enhancing mathematical reasoning and coding performance of large language models (LLMs) We investigate the effectiveness and scalability of RLVR across diverse real-world domains including medicine, chemistry, psychology, economics, and education. We utilize a generative scoring technique that yields soft, model-based reward signals to overcome limitations posed by binary verifications.
  arXiv  Detail & Related papers  (2025-03-31T08:22:49Z)
• LoXR: Performance Evaluation of Locally Executing LLMs on XR Devices [55.33807002543901]
  We deploy 17 large language models (LLMs) across four XR devices. We evaluate performance on four key metrics: performance consistency, processing speed, memory usage, and battery consumption.
  arXiv  Detail & Related papers  (2025-02-13T20:55:48Z)
• Explainable XR: Understanding User Behaviors of XR Environments using LLM-assisted Analytics Framework [24.02808692450192]
  We present Explainable XR, an end-to-end framework for analyzing user behavior in diverse XR environments. Explainable XR addresses challenges in handling cross-virtuality - AR, VR, MR - transitions, multi-user collaborative application scenarios.
  arXiv  Detail & Related papers  (2025-01-23T15:55:07Z)
• Software Testing for Extended Reality Applications: A Systematic Mapping Study [2.3418061477154786]
  Extended Reality (XR) is an emerging technology spanning diverse application domains and offering immersive user experiences. This paper presents the first systematic mapping study on software testing for XR applications.
  arXiv  Detail & Related papers  (2025-01-15T16:19:12Z)
• Advancing Extended Reality with 3D Gaussian Splatting: Innovations and Prospects [47.11223113086051]
  3D Gaussian Splatting (3DGS) has attracted significant attention for its potential to revolutionize 3D representation, rendering, and interaction.<n>Despite the rapid growth of 3DGS research, its direct application to Extended Reality (XR) remains underexplored.<n>In this paper, we aim to synthesize innovations in 3DGS that show specific potential for advancing XR research and development.
  arXiv  Detail & Related papers  (2024-12-09T07:14:58Z)
• RedStone: Curating General, Code, Math, and QA Data for Large Language Models [134.49774529790693]
  This study explores the untapped potential of Common Crawl as a comprehensive and flexible resource for pre-training Large Language Models.<n>We introduce RedStone, an innovative and scalable pipeline engineered to extract and process data from Common Crawl.
  arXiv  Detail & Related papers  (2024-12-04T15:27:39Z)
• FlashRAG: A Modular Toolkit for Efficient Retrieval-Augmented Generation Research [32.820100519805486]
  FlashRAG is an efficient and modular open-source toolkit designed to assist researchers in reproducing existing RAG methods and in developing their own RAG algorithms within a unified framework. Our toolkit has various features, including customizable modular framework, rich collection of pre-implemented RAG works, comprehensive datasets, efficient auxiliary pre-processing scripts, and extensive and standard evaluation metrics.
  arXiv  Detail & Related papers  (2024-05-22T12:12:40Z)
• A Performance Analysis Modeling Framework for Extended Reality Applications in Edge-Assisted Wireless Networks [22.191639532017724]
  Extended reality (XR) is at the center of attraction in the research community due to the emergence of augmented, mixed, and virtual reality applications. A comprehensive performance analysis model is required to assess the effectiveness of an XR application. We propose a novel modeling framework for performance analysis of XR applications considering edge-assisted wireless networks.
  arXiv  Detail & Related papers  (2024-05-11T15:16:12Z)
• Versatile User Identification in Extended Reality using Pretrained Similarity-Learning [16.356961801884562]
  We develop a similarity-learning model and pretrained it on the "Who Is Alyx?" dataset. In comparison with a traditional classification-learning baseline, our model shows superior performance. Our approach paves the way for easy integration of pretrained motion-based identification models in production XR systems.
  arXiv  Detail & Related papers  (2023-02-15T08:26:24Z)
• Benchmark Dataset and Effective Inter-Frame Alignment for Real-World Video Super-Resolution [65.20905703823965]
  Video super-resolution (VSR) aiming to reconstruct a high-resolution (HR) video from its low-resolution (LR) counterpart has made tremendous progress in recent years. It remains challenging to deploy existing VSR methods to real-world data with complex degradations. EAVSR takes the proposed multi-layer adaptive spatial transform network (MultiAdaSTN) to refine the offsets provided by the pre-trained optical flow estimation network.
  arXiv  Detail & Related papers  (2022-12-10T17:41:46Z)
• LaMAR: Benchmarking Localization and Mapping for Augmented Reality [80.23361950062302]
  We introduce LaMAR, a new benchmark with a comprehensive capture and GT pipeline that co-registers realistic trajectories and sensor streams captured by heterogeneous AR devices. We publish a benchmark dataset of diverse and large-scale scenes recorded with head-mounted and hand-held AR devices.
  arXiv  Detail & Related papers  (2022-10-19T17:58:17Z)
• Pyxis: An Open-Source Performance Dataset of Sparse Accelerators [10.18035715512647]
  PYXIS is a performance dataset for specialized accelerators on sparse data. PYXIS is open-source, and we are constantly growing PYXIS with new accelerator designs and performance statistics.
  arXiv  Detail & Related papers  (2021-10-08T17:46:51Z)
• A survey on applications of augmented, mixed and virtual reality for nature and environment [114.4879749449579]
  Augmented reality (AR), virtual reality (VR) and mixed reality (MR) are technologies of great potential due to the engaging and enriching experiences they are capable of providing. However, the possibilities that AR, VR and MR offer in the area of environmental applications are not yet widely explored. We present the outcome of a survey meant to discover and classify existing AR/VR/MR applications that can benefit the environment or increase awareness on environmental issues.
  arXiv  Detail & Related papers  (2020-08-27T09:59:27Z)

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.