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This project presents an exploration into 3D scene reconstruction ofsynthetic and real-world scenes using Neural Radiance Field (NeRF) approaches.We primarily take advantage of the reduction in training and rendering time ofneural graphic primitives multi-resolution hash encoding, to reconstruct staticvideo game scenes and real-world scenes, comparing and observing reconstructiondetail and limitations. Additionally, we explore dynamic scene reconstructionusing Neural Radiance Fields for Dynamic Scenes(D-NeRF). Finally, we extend theimplementation of D-NeRF, originally constrained to handle synthetic scenes toalso handle real-world dynamic scenes.

An Exploration of Neural Radiance Field Scene Reconstruction: Synthetic, Real-world and Dynamic Scenes