114 citations · 125 across the 5 of their papers we have counts for
5 papers
Optimizing Learned Image Compression on Scalar and Entropy-Constraint Quantization
Florian Borzechowski, Michael Schäfer, Heiko Schwarz +3
The continuous improvements on image compression with variational autoencoders have lead to learned codecs competitive with conventional approaches in terms of rate-distortion effi…
Adaptive Differential Filters for Fast and Communication-Efficient Federated Learning
Daniel Becking, Heiner Kirchhoffer, Gerhard Tech +4
Federated learning (FL) scenarios inherently generate a large communication overhead by frequently transmitting neural network updates between clients and server. To minimize the c…
DeepCABAC: A Universal Compression Algorithm for Deep Neural Networks
Simon Wiedemann, Heiner Kirchoffer, Stefan Matlage +10
The field of video compression has developed some of the most sophisticated and efficient compression algorithms known in the literature, enabling very high compressibility for lit…
DeepCABAC: Context-adaptive binary arithmetic coding for deep neural network compression
Simon Wiedemann, Heiner Kirchhoffer, Stefan Matlage +9
We present DeepCABAC, a novel context-adaptive binary arithmetic coder for compressing deep neural networks. It quantizes each weight parameter by minimizing a weighted rate-distor…
Image interpolation using Shearlet based iterative refinement
H. Lakshman, W. -Q Lim, H. Schwarz +3
This paper proposes an image interpolation algorithm exploiting sparse representation for natural images. It involves three main steps: (a) obtaining an initial estimate of the hig…