AirNeRF: 3D Reconstruction of Human with Drone and NeRF for Future Communication Systems

In the rapidly evolving landscape of digital content creation, the demand for fast, convenient, and autonomous methods of crafting detailed 3D reconstructions of humans has grown significantly. Addressing this pressing need, our AirNeRF system presents an innovative pathway to the creation of a realistic 3D human avatar. Our approach leverages Neural Radiance Fields (NeRF) with an automated drone-based video capturing method. The acquired data provides a swift and precise way to create high-quality human body reconstructions following several stages of our system. The rigged mesh derived from our system proves to be an excellent foundation for free-view synthesis of dynamic humans, particularly well-suited for the immersive experiences within gaming and virtual reality.

FlyNeRF: NeRF-Based Aerial Mapping for High-Quality 3D Scene Reconstruction

Current methods for 3D reconstruction and environmental mapping frequently face challenges in achieving high precision, highlighting the need for practical and effective solutions. In response to this issue, our study introduces FlyNeRF, a system integrating Neural Radiance Fields (NeRF) with drone-based data acquisition for high-quality 3D reconstruction. Utilizing unmanned aerial vehicle (UAV) for capturing images and corresponding spatial coordinates, the obtained data is subsequently used for the initial NeRF-based 3D reconstruction of the environment. Further evaluation of the reconstruction render quality is accomplished by the image evaluation neural network developed within the scope of our system. According to the results of the image evaluation module, an autonomous algorithm determines the position for additional image capture, thereby improving the reconstruction quality. The neural network introduced for render quality assessment demonstrates an accuracy of 97%. Furthermore, our adaptive methodology enhances the overall reconstruction quality, resulting in an average improvement of 2.5 dB in Peak Signal-to-Noise Ratio (PSNR) for the 10% quantile. The FlyNeRF demonstrates promising results, offering advancements in such fields as environmental monitoring, surveillance, and digital twins, where high-fidelity 3D reconstructions are crucial.