In recent years, the task of learned point cloud compression has gained
...
Entropy coding is essential to data compression, image and video coding,...
Image coding for machines (ICM) aims to compress images to support downs...
Learned image compression (LIC) methods have exhibited promising progres...
Recent state-of-the-art Learned Image Compression methods feature spatia...
Spectral Normalization is one of the best methods for stabilizing the
tr...
Most machine vision tasks (e.g., semantic segmentation) are based on ima...
Lossless image compression is an essential research field in image
compr...
Learned image compression allows achieving state-of-the-art accuracy and...
FPGA is appropriate for fix-point neural networks computing due to high ...
Learned image compression techniques have achieved considerable developm...
In this paper, we propose a learned video codec with a residual predicti...
Convolutional neural network (CNN)-based filters have achieved great suc...
We present a large challenging dataset, COUGH, for COVID-19 FAQ retrieva...
Convolutional Neural Network (CNN)-based filters have achieved significa...
In this paper, a dual learning-based method in intra coding is introduce...
Image compression has been investigated as a fundamental research topic ...