T. Shanableh

LRConv-NeRV: Low-Rank Convolution for Efficient Neural Video Compression

LRConv–NeRV, an efficient NeRV variant that replaces selected dense convolutional layers with structured low-rank separable convolutions, trained end-to-end within the decoder architecture, is proposed, establishing LRConv–NeRV as a potential architectural alternative for efficient neural video decoding under low-preci...