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Found 5 papers, 2 papers with code
Efficient Per-Shot Convex Hull Prediction By Recurrent Learning
Adaptive video streaming relies on the construction of efficient bitrate ladders to deliver the best possible visual quality to viewers under bandwidth constraints.
Self-Supervised Learning of Perceptually Optimized Block Motion Estimates for Video Compression
Block based motion estimation is integral to inter prediction processes performed in hybrid video codecs.
Perceptually Optimizing Deep Image Compression
Mean squared error (MSE) and $\ell_p$ norms have largely dominated the measurement of loss in neural networks due to their simplicity and analytical properties.
ProxIQA: A Proxy Approach to Perceptual Optimization of Learned Image Compression
By building on top of an existing deep image compression model, we are able to demonstrate a bitrate reduction of as much as $31\%$ over MSE optimization, given a specified perceptual quality (VMAF) level.
Speeding up VP9 Intra Encoder with Hierarchical Deep Learning Based Partition Prediction
In VP9 video codec, the sizes of blocks are decided during encoding by recursively partitioning 64$\times$64 superblocks using rate-distortion optimization (RDO).
