Elic: Efficient learned image compression with unevenly grouped space-channel contextual adaptive coding
Recently, learned image compression techniques have achieved remarkable performance,
even surpassing the best manually designed lossy image coders. They are promising to be …
even surpassing the best manually designed lossy image coders. They are promising to be …
Learned image compression with discretized gaussian mixture likelihoods and attention modules
Image compression is a fundamental research field and many well-known compression
standards have been developed for many decades. Recently, learned compression …
standards have been developed for many decades. Recently, learned compression …
Joint global and local hierarchical priors for learned image compression
Recently, learned image compression methods have outperformed traditional hand-crafted
ones including BPG. One of the keys to this success is learned entropy models that estimate …
ones including BPG. One of the keys to this success is learned entropy models that estimate …
[HTML][HTML] Reduced-complexity end-to-end variational autoencoder for on board satellite image compression
Recently, convolutional neural networks have been successfully applied to lossy image
compression. End-to-end optimized autoencoders, possibly variational, are able to …
compression. End-to-end optimized autoencoders, possibly variational, are able to …
Multi-scale attention-based pseudo-3D convolution neural network for Alzheimer's disease diagnosis using structural MRI
Recently, deep learning based Computer-Aided Diagnosis methods have been widely
utilized due to their highly effective diagnosis of patients. Although Convolutional Neural …
utilized due to their highly effective diagnosis of patients. Although Convolutional Neural …
Semantic-preserving image compression
Video traffic comprises a large majority of the total traffic on the internet today.
Uncompressed visual data requires a very large data rate; lossy compression techniques …
Uncompressed visual data requires a very large data rate; lossy compression techniques …
[HTML][HTML] Remote sensing image compression based on the multiple prior information
C Fu, B Du - Remote Sensing, 2023 - mdpi.com
Learned image compression has achieved a series of breakthroughs for nature images, but
there is little literature focusing on high-resolution remote sensing image (HRRSI) datasets …
there is little literature focusing on high-resolution remote sensing image (HRRSI) datasets …
3-d context entropy model for improved practical image compression
In this paper, we present our image compression framework designed for CLIC 2020
competition. Our method is based on Variational AutoEncoder (VAE) architecture which is …
competition. Our method is based on Variational AutoEncoder (VAE) architecture which is …
Deep learning video analytics through online learning based edge computing
Video analytics demand intensive computation resources, which means long processing
delay when running on mobile devices. Although offloading computation to the cloud can …
delay when running on mobile devices. Although offloading computation to the cloud can …
Learned image compression with fixed-point arithmetic
Learned image compression (LIC) has achieved superior coding performance than
traditional image compression standards such as HEVC intra in terms of both PSNR and MS …
traditional image compression standards such as HEVC intra in terms of both PSNR and MS …