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Found 12 papers, 0 papers with code
Low-Latency Neural Stereo Streaming
The rise of new video modalities like virtual reality or autonomous driving has increased the demand for efficient multi-view video compression methods, both in terms of rate-distortion (R-D) performance and in terms of delay and runtime.
Bitstream Organization for Parallel Entropy Coding on Neural Network-based Video Codecs
Video compression systems must support increasing bandwidth and data throughput at low cost and power, and can be limited by entropy coding bottlenecks.
New Filters for Image Interpolation and Resizing
We propose a new class of kernels to simplify the design of filters for image interpolation and resizing.
MobileNVC: Real-time 1080p Neural Video Compression on a Mobile Device
This work presents the first neural video codec that decodes 1080p YUV420 video in real time on a mobile device.
Differentiable bit-rate estimation for neural-based video codec enhancement
Neural networks (NN) can improve standard video compression by pre- and post-processing the encoded video.
Optimized learned entropy coding parameters for practical neural-based image and video compression
Neural-based image and video codecs are significantly more power-efficient when weights and activations are quantized to low-precision integers.
Boosting neural video codecs by exploiting hierarchical redundancy
In video compression, coding efficiency is improved by reusing pixels from previously decoded frames via motion and residual compensation.
MobileCodec: Neural Inter-frame Video Compression on Mobile Devices
Realizing the potential of neural video codecs on mobile devices is a big technological challenge due to the computational complexity of deep networks and the power-constrained mobile hardware.
Transform Network Architectures for Deep Learning based End-to-End Image/Video Coding in Subsampled Color Spaces
Most of the existing deep learning based end-to-end image/video coding (DLEC) architectures are designed for non-subsampled RGB color format.
Progressive Neural Image Compression with Nested Quantization and Latent Ordering
We present PLONQ, a progressive neural image compression scheme which pushes the boundary of variable bitrate compression by allowing quality scalable coding with a single bitstream.
Parallelized Rate-Distortion Optimized Quantization Using Deep Learning
We train two classes of neural networks, a fully-convolutional network and an auto-regressive network, and evaluate each as a post-quantization step designed to refine cheap quantization schemes such as scalar quantization (SQ).
Parametric Graph-based Separable Transforms for Video Coding
In many video coding systems, separable transforms (such as two-dimensional DCT-2) have been used to code block residual signals obtained after prediction.
