AHCI RESEARCH GROUP

Publications

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

OUR RESEARCH

Scientific Publications

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2023

Wang, Z.; Joshi, A.; Zhang, G.; Ren, W.; Jia, F.; Sun, X.

Elevating Perception: Unified Recognition Framework and Vision-Language Pre-Training Using Three-Dimensional Image Reconstruction Proceedings Article

In: Proc. - Int. Conf. Artif. Intell., Human-Comput. Interact. Robot., AIHCIR, pp. 592–596, Institute of Electrical and Electronics Engineers Inc., 2023, ISBN: 979-835036036-3 (ISBN).

Abstract | Links | BibTeX | Tags: 3D Model LLM, 3D modeling, 3D models, 3D Tech, 3d-modeling, Augmented Reality, Character recognition, Component, Computer aided design, Computer vision, Continuous time systems, Data handling, Generative AI, Image enhancement, Image Reconstruction, Image to Text Generation, Medical Imaging, Pattern recognition, Pre-training, Reconstructive Training, Text generations, Three dimensional computer graphics, Virtual Reality

@inproceedings{wang_elevating_2023,

title = {Elevating Perception: Unified Recognition Framework and Vision-Language Pre-Training Using Three-Dimensional Image Reconstruction},

author = {Z. Wang and A. Joshi and G. Zhang and W. Ren and F. Jia and X. Sun},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85192837757&doi=10.1109%2fAIHCIR61661.2023.00105&partnerID=40&md5=0fe17cc622a9aa90e88b8c3e6a3bed3b},

doi = {10.1109/AIHCIR61661.2023.00105},

isbn = {979-835036036-3 (ISBN)},

year  = {2023},

date = {2023-01-01},

booktitle = {Proc. - Int. Conf. Artif. Intell., Human-Comput. Interact. Robot., AIHCIR},

pages = {592–596},

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

abstract = {This research project explores a paradigm shift in perceptual enhancement by integrating a Unified Recognition Framework and Vision-Language Pre-Training in three-dimensional image reconstruction. Through the synergy of advanced algorithms from computer vision & language processing, the project tries to enhance the precision and depth of perception in reconstructed images. This innovative approach holds the potential to revolutionize fields such as medical imaging, virtual reality, and computer-aided design, providing a comprehensive perspective on the intersection of multimodal data processing and perceptual advancement. The anticipated research outcomes are expected to significantly contribute to the evolution of technologies that rely on accurate and contextually rich three-dimensional reconstructions. Moreover, the research aims to reduce the constant need for new datasets by improving pattern recognition through 3D image patterning on backpropagation. This continuous improvement of vectors is envisioned to enhance the efficiency and accuracy of pattern recognition, contributing to the optimization of perceptual systems over time. © 2023 IEEE.},

keywords = {3D Model LLM, 3D modeling, 3D models, 3D Tech, 3d-modeling, Augmented Reality, Character recognition, Component, Computer aided design, Computer vision, Continuous time systems, Data handling, Generative AI, Image enhancement, Image Reconstruction, Image to Text Generation, Medical Imaging, Pattern recognition, Pre-training, Reconstructive Training, Text generations, Three dimensional computer graphics, Virtual Reality},

pubstate = {published},

tppubtype = {inproceedings}

}