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Found 6 papers, 0 papers with code
Combining Progressive Rethinking and Collaborative Learning: A Deep Framework for In-Loop Filtering
For (2), we extract both intra-frame and inter-frame side information for better context modeling.
An Emerging Coding Paradigm VCM: A Scalable Coding Approach Beyond Feature and Signal
To this end, we make endeavors in leveraging the strength of predictive and generative models to support advanced compression techniques for both machine and human vision tasks simultaneously, in which visual features serve as a bridge to connect signal-level and task-level compact representations in a scalable manner.
A Comprehensive Benchmark for Single Image Compression Artifacts Reduction
We present a comprehensive study and evaluation of existing single image compression artifacts removal algorithms, using a new 4K resolution benchmark including diversified foreground objects and background scenes with rich structures, called Large-scale Ideal Ultra high definition 4K (LIU4K) benchmark.
Deep Reference Generation with Multi-Domain Hierarchical Constraints for Inter Prediction
In this paper, we address the problem by proposing a deep frame interpolation network to generate additional reference frames in coding scenarios.
A Group Variational Transformation Neural Network for Fractional Interpolation of Video Coding
Then a group variational transformation technique is used to transform a group of copied shared feature maps to samples at different sub-pixel positions.
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Dual Recovery Network with Online Compensation for Image Super-Resolution
In particular, we infer the HF information based on both the LR image and similar HR references which are retrieved online.
