SOTAVerified

Video Compression

Video Compression is a process of reducing the size of an image or video file by exploiting spatial and temporal redundancies within an image or video frame and across multiple video frames. The ultimate goal of a successful Video Compression system is to reduce data volume while retaining the perceptual quality of the decompressed data.

Source: Adversarial Video Compression Guided by Soft Edge Detection

Papers

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Showing 351–400 of 496 papers

TitleStatusHype
Recursive Fusion and Deformable Spatiotemporal Attention for Video Compression Artifact ReductionCode0
Insights from Generative Modeling for Neural Video CompressionCode0
Neural Video Compression using GANs for Detail Synthesis and Propagation—0
Objective video quality metrics application to video codecs comparisons: choosing the best for subjective quality estimation—0
RCLC: ROI-based joint conventional and learning video compressionCode0
Comparison of Lossless Image Formats—0
Multiview Video Compression Using Advanced HEVC Screen Content Coding—0
FOVQA: Blind Foveated Video Quality Assessment—0
Revisit Visual Representation in Analytics Taxonomy: A Compression Perspective—0
Quality assessment methods for perceptual video compression—0
Perceptually-inspired super-resolution of compressed videos—0
An adaptive Lagrange multiplier determination method for rate-distortion optimisation in hybrid video codecs—0
Evaluating Foveated Video Quality Using Entropic Differencing—0
Boosting the Performance of Video Compression Artifact Reduction with Reference Frame Proposals and Frequency Domain Information—0
Towards Transparent Application of Machine Learning in Video Processing—0
Convolutional Block Design for Learned Fractional Downsampling—0
A Practical Approach for Rate-Distortion-Perception Analysis in Learned Image Compression—0
ELF-VC: Efficient Learned Flexible-Rate Video Coding—0
Conditional Coding for Flexible Learned Video Compression—0
Multi-Density Attention Network for Loop Filtering in Video Compression—0
Joint Optimization for SSIM-Based CTU-Level Bit Allocation and Rate Distortion OptimizationCode0
Lossless compression with state space models using bits back codingCode0
SCALE SPACE FLOW WITH AUTOREGRESSIVE PRIORS—0
Texture-aware Video Frame Interpolation—0
Just Noticeable Difference for Deep Machine Vision—0
B-DRRN: A Block Information Constrained Deep Recursive Residual Network for Video Compression Artifacts ReductionCode0
Video Question Answering Using Language-Guided Deep Compressed-Domain Video Feature—0
Online-Trained Upsampler for Deep Low Complexity Video Compression—0
Parallelized Rate-Distortion Optimized Quantization Using Deep Learning—0
Decomposition, Compression, and Synthesis (DCS)-based Video Coding: A Neural Exploration via Resolution-Adaptive Learning—0
Ultra-low bitrate video conferencing using deep image animationCode0
Generative Video Compression as Hierarchical Variational Inference—0
CVEGAN: A Perceptually-inspired GAN for Compressed Video EnhancementCode0
Light Field Compression by Residual CNN Assisted JPEGCode0
Learning to Compress Videos without Computing MotionCode0
Lossless White Balance For Improved Lossless CFA Image and Video Compression—0
Video Compression with CNN-based Post Processing—0
Improving Deep Video Compression by Resolution-adaptive Flow Coding—0
Inpainting-based Video Compression in FullHD—0
Conditional Entropy Coding for Efficient Video Compression—0
A Technical Overview of AV1—0
End-to-End Rate-Distortion Optimization for Bi-Directional Learned Video Compression—0
Deep Multi-modality Soft-decoding of Very Low Bit-rate Face Videos—0
High-quality Single-model Deep Video Compression with Frame-Conv3D and Multi-frame Differential Modulation—0
Video compression with low complexity CNN-based spatial resolution adaptation—0
On the Impact of Lossy Image and Video Compression on the Performance of Deep Convolutional Neural Network Architectures—0
Efficient Adaptation of Neural Network Filter for Video Compression—0
Using modern motion estimation algorithms in existing video codecs—0
MFRNet: A New CNN Architecture for Post-Processing and In-loop Filtering—0
Neural Video Coding using Multiscale Motion Compensation and Spatiotemporal Context Model—0
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