[R] Wavelet Feature Maps Compression for Image-to-Image CNNs

Our NeurIPS 2022 paper "Wavelet Feature Maps Compression for Image-to-Image CNNs" is now available.


In this paper, we propose a novel approach to compress CNNs using a modified wavelet compression technique.


Abstract:

>Convolutional Neural Networks (CNNs) are known for requiring extensive computational resources, and quantization is among the best and most common methods for compressing them. While aggressive quantization (i.e., less than 4-bits) performs well for classification, it may cause severe performance degradation in image-to-image tasks such as semantic segmentation …

cnns compression feature image machinelearning maps wavelet