"CNN"

HEVC VMAF-oriented Perceptual Rate Distortion Optimization using CNN

Video coding standards like HEVC and VVC have achieved significant coding performance. However, the RDO module in coding framework ignores the characteristics of human visual system (HVS), which leads to insufficiency for perceptual video coding. …

Deep Feature Guided Image Retargeting

Image retargeting is the technique to display images via devices with various aspect ratios and sizes. Traditional content-aware retargeting methods rely on low-level features to predict pixel-wise importance and can hardly preserve both the …

A Generic Method to Improve No-Reference Image Blur Metric Accuracy in Video Contents

We present in this work a generic and effective method to increase the prediction accuracy of no-reference image/video blur assessment facing the real-world content diversity. We demonstrate that benchmarking no reference image blur metrics, fitting …

CNN based post-processing to improve HEVC

In this paper, we propose a frame-based dynamic metadata post-processing scheme in HEVC. Video sequence is classified into different categories contains complexity of video content and quality indicator for each frame, an up-to-one byte flag embedded …

Deep hash learning for efficient image retrieval

Hashing method is a widely used method for content-based image retrieval. For more complicated semantic similarity of images, supervised hashing methods based on hand-crafted features show its limitations. Convolutional neural network (CNN) has …

Two-stream recurrent convolutional neural networks for video saliency estimation

Recently, research has emphasized the need for video saliency estimation since its application covers a large domain. Traditional saliency prediction methods for video based on hand-crafted visual features lead to slow speed and ineffective results. …