  The advances in the Neural Radiance Fields (NeRF) research offer extensive
applications in diverse domains, but protecting their copyrights has not yet
been researched in depth. Recently, NeRF watermarking has been considered one
of the pivotal solutions for safely deploying NeRF-based 3D representations.
However, existing methods are designed to apply only to implicit or explicit
NeRF representations. In this work, we introduce an innovative watermarking
method that can be employed in both representations of NeRF. This is achieved
by fine-tuning NeRF to embed binary messages in the rendering process. In
detail, we propose utilizing the discrete wavelet transform in the NeRF space
for watermarking. Furthermore, we adopt a deferred back-propagation technique
and introduce a combination with the patch-wise loss to improve rendering
quality and bit accuracy with minimum trade-offs. We evaluate our method in
three different aspects: capacity, invisibility, and robustness of the embedded
watermarks in the 2D-rendered images. Our method achieves state-of-the-art
performance with faster training speed over the compared state-of-the-art
methods.
