570 citations · 3k across the 41 of their papers we have counts for
10 papers · 1 filter
Implicit Neural Video Compression
Yunfan Zhang, Ties van Rozendaal, Johann Brehmer +2
We propose a method to compress full-resolution video sequences with implicit neural representations. Each frame is represented as a neural network that maps coordinate positions t…
Instance-Adaptive Video Compression: Improving Neural Codecs by Training on the Test Set
Ties van Rozendaal, Johann Brehmer, Yunfan Zhang +3
We introduce a video compression algorithm based on instance-adaptive learning. On each video sequence to be transmitted, we finetune a pretrained compression model. The optimal pa…
Efficient Neural Causal Discovery without Acyclicity Constraints
Phillip Lippe, Taco Cohen, Efstratios Gavves
Learning the structure of a causal graphical model using both observational and interventional data is a fundamental problem in many scientific fields. A promising direction is con…
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Michael M. Bronstein, Joan Bruna, Taco Cohen +1
The last decade has witnessed an experimental revolution in data science and machine learning, epitomised by deep learning methods. Indeed, many high-dimensional learning tasks pre…
Skip-Convolutions for Efficient Video Processing
Amirhossein Habibian, Davide Abati, Taco S. Cohen +1
We propose Skip-Convolutions to leverage the large amount of redundancies in video streams and save computations. Each video is represented as a series of changes across frames and…
A Combined Deep Learning based End-to-End Video Coding Architecture for YUV Color Space
Ankitesh K. Singh, Hilmi E. Egilmez, Reza Pourreza +3
Most of the existing deep learning based end-to-end video coding (DLEC) architectures are designed specifically for RGB color format, yet the video coding standards, including H.26…