Despite the tremendous success of diffusion generative models in
text-to...
We show how bidirectional transformers trained for masked token predicti...
By optimizing the rate-distortion-realism trade-off, generative compress...
We describe a novel lossy compression approach called DiffC which is bas...
We show how transformers can be used to vastly simplify neural video
com...
We present a neural video compression method based on generative adversa...
The past few years have witnessed increasing interests in applying deep
...
We extensively study how to combine Generative Adversarial Networks and
...
We leverage the powerful lossy image compression algorithm BPG to build ...
The recent years have witnessed the great potential of deep learning for...
We propose the first practical learned lossless image compression system...
We propose a framework for extreme learned image compression based on
Ge...
Motivated by recent work on deep neural network (DNN)-based image compre...
Deep Neural Networks trained as image auto-encoders have recently emerge...
We present a new approach to learn compressible representations in deep
...
We propose a highly structured neural network architecture for semantic
...