19 citations · 42 across the 7 of their papers we have counts for
8 papers
MobileCodec: Neural Inter-frame Video Compression on Mobile Devices
Hoang Le, Liang Zhang, Amir Said +6
Realizing the potential of neural video codecs on mobile devices is a big technological challenge due to the computational complexity of deep networks and the power-constrained mob…
Region-of-Interest Based Neural Video Compression
Yura Perugachi-Diaz, Guillaume Sautière, Davide Abati +3
Humans do not perceive all parts of a scene with the same resolution, but rather focus on few regions of interest (ROIs). Traditional Object-Based codecs take advantage of this bio…
Transform Network Architectures for Deep Learning based End-to-End Image/Video Coding in Subsampled Color Spaces
Hilmi E. Egilmez, Ankitesh K. Singh, Muhammed Coban +5
Most of the existing deep learning based end-to-end image/video coding (DLEC) architectures are designed for non-subsampled RGB color format. However, in order to achieve a superio…
Progressive Neural Image Compression with Nested Quantization and Latent Ordering
Yadong Lu, Yinhao Zhu, Yang Yang +2
We present PLONQ, a progressive neural image compression scheme which pushes the boundary of variable bitrate compression by allowing quality scalable coding with a single bitstrea…
Feedback Recurrent Autoencoder for Video Compression
Adam Golinski, Reza Pourreza, Yang Yang +2
Recent advances in deep generative modeling have enabled efficient modeling of high dimensional data distributions and opened up a new horizon for solving data compression problems…
Guided Variational Autoencoder for Disentanglement Learning
Zheng Ding, Yifan Xu, Weijian Xu +4
We propose an algorithm, guided variational autoencoder (Guided-VAE), that is able to learn a controllable generative model by performing latent representation disentanglement lear…