QRF: Implicit Neural Representations with Quantum Radiance Fields

Photorealistic rendering of real-world scenes is a tremendous challenge with a wide range of applications, including mixed reality (MR), and virtual reality (VR). Neural networks, which have long been investigated in the context of solving differential equations, have previously been introduced as implicit representations for photorealistic rendering. However, realistic rendering using classic computing is challenging because it requires time-consuming optical ray marching, and suffer computational bottlenecks due to the curse of dimensionality. In this paper, we propose Quantum Radiance Fields (QRF), which integrate the quantum circuit, quantum activation function, and quantum volume rendering for implicit scene representation. The results indicate that QRF not only exploits the advantage of quantum computing, such as high speed, fast convergence, and high parallelism, but also ensure high quality of volume rendering.