Work

3D Image Generation Model Using GAN

Year: 2025

Type: article

Abstract: This project presents a 3D Image Generation Model using Generative Adversarial Networks (GANs).The model was deve;oped and trained using a custom dataset to produce realistic 3D image outputs. The aim is to enhance the performance and accuracy of 3D image synthesis for use in apllications such as virtual reality and game development. This repository inclides the trained model, source code, and supporting documentation for reproducibility and further research.3D

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.15429452

Authors: Vaibhav Sanjay Bagekari, Vaibhav Sanjay Bagekari, Ashlesha Rajendra Yadav, Ashlesha Rajendra Yadav, Prajakta Sambhaji Bhorde, Prajakta Sambhaji Bhorde, Puja Anil Kare, Puja Anil Kare

Language: English

Topic: Generative Adversarial Networks and Image Synthesis

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W6949714167

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