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Positional encodings are employed to capture the high frequency informationof the encoded signals in implicit neural representation (INR). In this paper,we propose a novel positional encoding method which improves the reconstructionquality of the INR. The proposed embedding method is more advantageous for thecompact data representation because it has a greater number of frequency basisthan the existing methods. Our experiments shows that the proposed methodachieves significant gain in the rate-distortion performance withoutintroducing any additional complexity in the compression task and higherreconstruction quality in novel view synthesis.

Improved Positional Encoding for Implicit Neural Representation based Compact Data Representation