Deep Learning-Based Object Recognition in AR-VR Environment
Artificial intelligence (AI), AR-VR (Augmented Reality and Virtual Reality) have recently made significant strides, paving the way for innovation and change in a wide range of fields and industries. The quick advancements in AR-VR and computer vision (CV) made it easier to comprehend and analyze the surroundings. In this study, works that combined augmented, virtual reality (AR-VR) and deep learning for object recognition throughout the recent years are thoroughly reviewed and presented. The three primary focuses of this paper are: 1) List out the object identification techniques used in AR-VR in detail, 2) Describe the techniques, tools, and frameworks that are being utilized to create various types of AR- VR object detection, 3) Discussing object detection in AR-VR in detail and 4) Concluding the problems and identifying possible study fields in the AR-VR environment.
Authors
- Manoj Diwakar (ORCID: https://orcid.org/0000-0002-4435-675X)
- Prabhishek Singh (ORCID: https://orcid.org/0000-0002-9338-0932)
- G Mehra (ORCID: https://orcid.org/0009-0008-0585-5477)
- Pankaj Kumar (ORCID: https://orcid.org/0000-0001-5603-2691)
- Aditya Joshi (ORCID: https://orcid.org/0000-0003-4392-5401)
- Suchi Sharma
Institutions
- Bennett University (IN)
- Graphic Era University (IN)
Publication Details
- Published
- 2025-02-13
- DOI
- https://doi.org/10.1109/ic363308.2025.10956766
- Citations
- 1
- Primary Topic
- Robotics and Automated Systems
- Type
- article
- Field-Weighted Citation Impact
- 1.21