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A Residual Diffusion Model for High Perceptual Quality Codec Augmentation
Diffusion probabilistic models have recently achieved remarkable success in generating high quality image and video data.
Region-of-Interest Based Neural Video Compression
To the best of our knowledge, our proposals are the first solutions that integrate ROI-based capabilities into neural video compression models.
Lossy Compression with Distortion Constrained Optimization
We argue that the constrained optimization method of Rezende and Viola, 2018 is a lot more appropriate for training lossy compression models because it allows us to obtain the best possible rate subject to a distortion constraint.
Feedback Recurrent AutoEncoder
In this work, we propose a new recurrent autoencoder architecture, termed Feedback Recurrent AutoEncoder (FRAE), for online compression of sequential data with temporal dependency.
