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Found 7 papers, 3 papers with code
Improved CNN-based Learning of Interpolation Filters for Low-Complexity Inter Prediction in Video Coding
The approach requires a single neural network to be trained from which a full quarter-pixel interpolation filter set is derived, as the network is easily interpretable due to its linear structure.
Attention-Based Neural Networks for Chroma Intra Prediction in Video Coding
Simplifications include a framework for reducing the overhead of the convolutional operations, a simplified cross-component processing model integrated into the original architecture, and a methodology to perform integer-precision approximations with the aim to obtain fast and hardware-aware implementations.
Chroma Intra Prediction with attention-based CNN architectures
Neural networks can be used in video coding to improve chroma intra-prediction.
Interpreting CNN for Low Complexity Learned Sub-pixel Motion Compensation in Video Coding
Deep learning has shown great potential in image and video compression tasks.
Analytic Simplification of Neural Network based Intra-Prediction Modes for Video Compression
With the increasing demand for video content at higher resolutions, it is evermore critical to find ways to limit the complexity of video encoding tasks in order to reduce costs, power consumption and environmental impact of video services.
Estimation of Rate Control Parameters for Video Coding Using CNN
As reference frames are essential for exploiting temporal redundancies, intra frames are usually assigned a larger portion of the available bits.
Convolutional Neural Networks for Video Quality Assessment
Moreover, transmission also introduces delays and other distortion types which affect the perceived quality.
