Abstract

Image-Based Rendering (IBR) techniques have become essential for generating realistic and immersive visual content, allowing users to explore scenes from different viewpoints. This research paper proposes an innovative framework, named Intelligent Image-Based Rendering (iIBR), that harnesses the power of machine learning to enhance IBR capabilities. The framework integrates deep learning models, reinforcement learning algorithms, and generative networks to address challenges related to view synthesis, scene completion, and virtual scene realism. Through extensive evaluation and comparisons with traditional IBR approaches, the iIBR framework demonstrates superior performance, adaptability, and potential applications in virtual reality, gaming, cinematography, architectural visualization, and beyond.

Keywords: Image-based rendering, Machine learning, Deep learning, Reinforcement learning, Generative networks, View synthesis, Scene completion, Realism, Virtual reality, Gaming, Cinematography, Architectural visualization