HOSNeRF: an AI model that can generate dynamic neural radiance fields from

This paper describes a new approach to view synthesis based on neural radiance fields, previously used in radar and optoelectrics.

The goal of the paper is to create a framework that enables 360° freeviewpoint high-fidelity novel view synthesis for dynamic scenes with human-environment interactions within a single video.

Significant progress has been made in the field of view synthesis using neural ray tracing, with NeRF playing a pivotal role.

However, the challenges in this area have been greatly improved since its inception.

This paper seeks to address the challenge of dynamic view synthesis by incorporating dynamic elements such as deformation fields and spatiotemporal radiance Fields into the viewscreens.

It uses a unique approach called High-Object-Scene Neural Radiance Fields (HOSNeRF) to overcome the limitations of NeRF.

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