High-Fidelity Synthetic Data Generation Framework for Unique Objects Detection

High-Fidelity Synthetic Data Generation Framework for Unique Objects Detection

One of the key barriers to neural network adoption is the lack of computational resources and high-quality training data—particularly for unique objects without existing datasets. This research explores methods for generating realistic synthetic images that preserve the visual properties of target o...

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Bibliographic Details
Main Authors: Nataliya Shakhovska, Bohdan Sydor, Solomiia Liaskovska, Olga Duran, Yevgen Martyn, Volodymyr Vira
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Computation
Subjects:
neural networks
diffusion generative models
synthetic training data
3D reconstruction
Online Access:https://www.mdpi.com/2079-3197/13/5/120
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