AHCI RESEARCH GROUP

Publications

Papers published in international journals,
proceedings of conferences, workshops and books.

OUR RESEARCH

Scientific Publications

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2024

Kim, S. J.; Cao, D. D.; Spinola, F.; Lee, S. J.; Cho, K. S.

RoomRecon: High-Quality Textured Room Layout Reconstruction on Mobile Devices Proceedings Article

In: U., Eck; M., Sra; J., Stefanucci; M., Sugimoto; M., Tatzgern; I., Williams (Ed.): Proc. - IEEE Int. Symp. Mixed Augment. Real., ISMAR, pp. 544–553, Institute of Electrical and Electronics Engineers Inc., 2024, ISBN: 979-833151647-5 (ISBN).

Abstract | Links | BibTeX | Tags: 3D modeling, 3D models, 3D reconstruction, 3d-modeling, AR-assisted image capturing, Architectural design, Augmented Reality, Augmented reality-assisted image capturing, Image capturing, Indoor 3D reconstruction, Indoor space, Mobile application, Mobile Applications, Mortar, Room layout, Texturing, Texturing quality

@inproceedings{kim_roomrecon_2024,

title = {RoomRecon: High-Quality Textured Room Layout Reconstruction on Mobile Devices},

author = {S. J. Kim and D. D. Cao and F. Spinola and S. J. Lee and K. S. Cho},

editor = {Eck U. and Sra M. and Stefanucci J. and Sugimoto M. and Tatzgern M. and Williams I.},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85213494599&doi=10.1109%2fISMAR62088.2024.00069&partnerID=40&md5=0f6b9d4c44d9c55cafba7ad76651ea07},

doi = {10.1109/ISMAR62088.2024.00069},

isbn = {979-833151647-5 (ISBN)},

year  = {2024},

date = {2024-01-01},

booktitle = {Proc. - IEEE Int. Symp. Mixed Augment. Real., ISMAR},

pages = {544–553},

publisher = {Institute of Electrical and Electronics Engineers Inc.},

abstract = {Widespread RGB-Depth (RGB-D) sensors and advanced 3D reconstruction technologies facilitate the capture of indoor spaces, improving the fields of augmented reality (AR), virtual reality (VR), and extended reality (XR). Nevertheless, current technologies still face limitations, such as the inability to reflect minor scene changes without a complete recapture, the lack of semantic scene understanding, and various texturing challenges that affect the 3D model's visual quality. These issues affect the realism required for VR experiences and other applications such as in interior design and real estate. To address these challenges, we introduce RoomRecon, an interactive, real-time scanning and texturing pipeline for 3D room models. We propose a two-phase texturing pipeline that integrates AR-guided image capturing for texturing and generative AI models to improve texturing quality and provide better replicas of indoor spaces. Moreover, we suggest to focus only on permanent room elements such as walls, floors, and ceilings, to allow for easily customizable 3D models. We conduct experiments in a variety of indoor spaces to assess the texturing quality and speed of our method. The quantitative results and user study demonstrate that RoomRecon surpasses state-of-the-art methods in terms of texturing quality and on-device computation time. © 2024 IEEE.},

keywords = {3D modeling, 3D models, 3D reconstruction, 3d-modeling, AR-assisted image capturing, Architectural design, Augmented Reality, Augmented reality-assisted image capturing, Image capturing, Indoor 3D reconstruction, Indoor space, Mobile application, Mobile Applications, Mortar, Room layout, Texturing, Texturing quality},

pubstate = {published},

tppubtype = {inproceedings}

}

2023

Le, M. -H.; Chu, C. -B.; Le, K. -D.; Nguyen, T. V.; Tran, M. -T.; Le, T. -N.

VIDES: Virtual Interior Design via Natural Language and Visual Guidance Proceedings Article

In: G., Bruder; A.H., Olivier; A., Cunningham; E.Y., Peng; J., Grubert; I., Williams (Ed.): Proc. - IEEE Int. Symp. Mixed Augment. Real. Adjunct, ISMAR-Adjunct, pp. 689–694, Institute of Electrical and Electronics Engineers Inc., 2023, ISBN: 979-835032891-2 (ISBN).

Abstract | Links | BibTeX | Tags: Architectural design, Customisation, Cutting edge technology, Design concept, Design systems, Image editing, Image generation, Image generations, Indoor space, Interior Design, Interior designs, Interiors (building), Natural languages, Virtual Reality, Visual guidance, Visual languages

@inproceedings{le_vides_2023,

title = {VIDES: Virtual Interior Design via Natural Language and Visual Guidance},

author = {M. -H. Le and C. -B. Chu and K. -D. Le and T. V. Nguyen and M. -T. Tran and T. -N. Le},

editor = {Bruder G. and Olivier A.H. and Cunningham A. and Peng E.Y. and Grubert J. and Williams I.},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85180376943&doi=10.1109%2fISMAR-Adjunct60411.2023.00148&partnerID=40&md5=5ce45d9e97fc5a9fdc31eb7514b3def3},

doi = {10.1109/ISMAR-Adjunct60411.2023.00148},

isbn = {979-835032891-2 (ISBN)},

year  = {2023},

date = {2023-01-01},

booktitle = {Proc. - IEEE Int. Symp. Mixed Augment. Real. Adjunct, ISMAR-Adjunct},

pages = {689–694},

publisher = {Institute of Electrical and Electronics Engineers Inc.},

abstract = {Interior design is crucial in creating aesthetically pleasing and functional indoor spaces. However, developing and editing interior design concepts requires significant time and expertise. We propose Virtual Interior DESign (VIDES) system in response to this challenge. Leveraging cutting-edge technology in generative AI, our system can assist users in generating and editing indoor scene concepts quickly, given user text description and visual guidance. Using both visual guidance and language as the conditional inputs significantly enhances the accuracy and coherence of the generated scenes, resulting in visually appealing designs. Through extensive experimentation, we demonstrate the effectiveness of VIDES in developing new indoor concepts, changing indoor styles, and replacing and removing interior objects. The system successfully captures the essence of users' descriptions while providing flexibility for customization. Consequently, this system can potentially reduce the entry barrier for indoor design, making it more accessible to users with limited technical skills and reducing the time required to create high-quality images. Individuals who have a background in design can now easily communicate their ideas visually and effectively present their design concepts. © 2023 IEEE.},

keywords = {Architectural design, Customisation, Cutting edge technology, Design concept, Design systems, Image editing, Image generation, Image generations, Indoor space, Interior Design, Interior designs, Interiors (building), Natural languages, Virtual Reality, Visual guidance, Visual languages},

pubstate = {published},

tppubtype = {inproceedings}

}