  Multiple Description Coding (MDC) is an error-resilient source coding method
designed for transmission over noisy channels. We present a novel MDC scheme
employing a neural network based on implicit neural representation. This
involves overfitting the neural representation for images. Each description is
transmitted along with model parameters and its respective latent spaces. Our
method has advantages over traditional MDC that utilizes auto-encoders, such as
eliminating the need for model training and offering high flexibility in
redundancy adjustment. Experiments demonstrate that our solution is competitive
with autoencoder-based MDC and classic MDC based on HEVC, delivering superior
visual quality.
