Towards Digital Twins of 3D Reconstructed Apparel Models with an End-to-End Mobile Visualization
Round 1
Reviewer 1 Report
The main question addressed by the authors is to provide a system that makes use of cloud computing resources to offload the resource-intensive activities of 3D reconstruction and deep learning-based scene interpretation.
It is an original and relevant topic because the researchers investigate the capability of mobile devices for the photo collection, cloud processing, and deep learning-based 3D generation, with seamless display in virtual reality (VR) wearables.
The findings of the research unveil an end-to-end pipeline from 2D to 3D-Reconstructed which automatically builds accurate 3D models from collected photographs using sophisticated deep-learning techniques.
The improvements that the authors have to consider are about the material's resolution, which may result in certain items that are not as attractive as expected.
The conclusions are consistent with the evidence and arguments presented and do they address the main question posed.
The references are appropriate.
Author Response
July 14, 2023
To Editor and Reviewers,
Thank you for giving us the opportunity to revise our manuscript. We have addressed each single valuable comment from the Reviewers. All the modifications in our paper have been highlighted in red in the revised manuscript. Any further suggestions you may have will be highly appreciated.
Thank you again for considering this paper for publication in the special issue "Virtual/Augmented Reality and Its Applications" of Computing and Artificial Intelligence.
Sincerely,
Mr. Surasachai Doungtap
Corresponding author: Jenq-Haur Wang (e-mail: [email protected])
National Taipei University of Technology
Author Response File: 
Author Response.pdf
Reviewer 2 Report
The research idea presented in the paper focuses on leveraging digital twin technologies, mobile devices, cloud computing, and deep learning for 3D reconstruction and virtual reality (VR) experiences. While the idea seems promising, there are a few aspects upon addressing could improve the paper.
1. Novelty: The paper claims to present a novel approach but does not clearly state how it differs from existing methods or what new contributions it brings to the field. It would benefit the authors to highlight their work's novel aspects explicitly.
2. Clear research objectives: The paper mentions facilitating daily-life activities and offloading resource-intensive tasks but does not clearly articulate the specific problem or research question being addressed. It would be helpful for the authors to define their study's objectives and research scope clearly.
3. Insufficient validation: In the experimental results, the paper does not provide sufficient details on the methodology, datasets used, or performance metrics employed. Without proper evaluation and validation, it is difficult to assess the effectiveness and reliability of the proposed approach.
4. Missing comparison with existing methods: The paper does not mention any comparative analysis with current techniques or benchmarks in the field. Without such comparisons, it is challenging to determine the advantages or disadvantages of the proposed approach over alternative methods.
5. Insufficient explanation of technical details: The paper briefly mentions deep learning techniques and cloud processing but does not provide enough technical details about the algorithms or architectures employed. Providing more information about the deep learning models and cloud computing infrastructure used would enhance the clarity and reproducibility of the research.
While the research idea presented in the paper shows potential, I believe it would benefit from addressing the critiques above to improve clarity, novelty, validation, and the overall quality of the study.
Comments for author File: Comments.pdf
Minor spell check and grammar correction is suggested.
Author Response
July 14, 2023
To Editor and Reviewers,
Thank you for giving us the opportunity to revise our manuscript. We have addressed each single valuable comment from the Reviewers. All the modifications in our paper have been highlighted in red in the revised manuscript. Any further suggestions you may have will be highly appreciated.
Thank you again for considering this paper for publication in the special issue "Virtual/Augmented Reality and Its Applications" of Computing and Artificial Intelligence.
Sincerely,
Mr. Surasachai Doungtap
Corresponding author: Jenq-Haur Wang (e-mail: [email protected])
National Taipei University of Technology
Author Response File: Author Response.pdf
Round 2
Reviewer 2 Report
I appreciate the author's effort in incorporating the suggested changes.
