Positional encodings are employed to capture the high frequency information of the encoded signals in implicit neural representation (INR). In this paper, we propose a novel positional encoding method which improves the reconstruction quality of the INR. The proposed embedding method is more advantageous for the compact data representation because it has a greater number of frequency basis than the existing methods. Our experiments shows that the proposed method achieves significant gain in the rate-distortion performance without introducing any additional complexity in the compression task and higher reconstruction quality in novel view synthesis.

翻译：位置编码用于捕获隐式神经表示（INR）中编码信号的高频信息。本文提出一种新颖的位置编码方法，可提升INR的重建质量。由于所提出的嵌入方法比现有方法拥有更多频率基函数，因此更有利于紧凑数据表示。实验表明，该方法在不增加压缩任务额外复杂度的前提下，显著提升了率失真性能，并在新视角合成任务中实现了更高的重建质量。