Evaluation metrics for intelligent generation of graphical game assets: a systematic survey-based framework

K Fukaya, D Daylamani-Zad… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Generative systems for graphical assets have the potential to provide users with high quality
assets at the push of a button. However, there are many forms of assets, and many …

Understanding user behavior in volumetric video watching: Dataset, analysis and prediction

K Hu, H Yang, Y **, J Liu, Y Chen, M Zhang… - Proceedings of the 31st …, 2023 - dl.acm.org
Volumetric video emerges as a new attractive video paradigm in recent years since it
provides an immersive and interactive 3D viewing experience with six degree-of-freedom …

Intelligent generation of graphical game assets: A conceptual framework and systematic review of the state of the art

K Fukaya, D Daylamani-Zad, H Agius - arxiv preprint arxiv:2311.10129, 2023 - arxiv.org
Procedural content generation (PCG) can be applied to a wide variety of tasks in games,
from narratives, levels and sounds, to trees and weapons. A large amount of game content is …

Intelligent Generation of Graphical Game Assets: A Conceptual Framework and Systematic Review of the State of the Art

K Fukaya, D Daylamani-Zad, H Agius - ACM Computing Surveys, 2025 - dl.acm.org
Procedural content generation (PCG) can be applied to a wide variety of tasks in games,
from narratives, levels, and sounds to trees and weapons. A large amount of game content is …

Development of a Non-Contact Sensor System for Converting 2D Images into 3D Body Data: A Deep Learning Approach to Monitor Obesity and Body Shape in …

JY Lee, K Kwon, C Kim, S Youm - Sensors, 2024 - mdpi.com
This study demonstrates how to generate a three-dimensional (3D) body model through a
small number of images and derive body values similar to the actual values using generated …

Multi-view Pixel2Mesh++: 3D reconstruction via Pixel2Mesh with more images

R Chen, X Yin, Y Yang, C Tong - The Visual Computer, 2023 - Springer
To meet the increasing demand for high-quality 3D models, we propose an end-to-end deep
learning network architecture, which can generate 3D mesh models with multiple RGB …

3D reconstruction of coronary arteries using deep networks from synthetic X-ray angiogram data

İ Atlı, OS Gedik - Communications Faculty of Sciences University of …, 2022 - dergipark.org.tr
Cardiovascular disease (CVD) is one of the most common health problems that are
responsible for one-third of all deaths around the globe. Although X-Ray angiography has …

Development of 3D body shape creation methodology for obesity information and body shape management for tracking body condition check: body type in their 20s …

C Kim, S Youm - 2022 - researchsquare.com
This paper demonstrates how to generate a three-dimensional (3D) body model through a
small number of images and derive body values​​ similar to the actual values​​ by using …

Application of machine learning in geodetic photogrammetric measurements

P Matyáš - 2024 - dspace.cvut.cz
This work provides a review of modern methods of usage machine and deep learning in
spatial information reconstruction with photogrammetric techniques and using these tools for …

3D Reconstruction from A Single Image

G **, H Wang - … on Cybernetics and Intelligent Systems (CIS) …, 2019 - ieeexplore.ieee.org
3D reconstruction is a field of computer vision. The last decade has seen great interest in
multi-images 3D reconstruction, and proposed some classic algorithms such as SFM …