27 citations · 53 across the 7 of their papers we have counts for
11 papers · 1 filter
AIM 2024 Challenge on Efficient Video Super-Resolution for AV1 Compressed Content
Marcos V Conde, Zhijun Lei, Wen Li +3
Video super-resolution (VSR) is a critical task for enhancing low-bitrate and low-resolution videos, particularly in streaming applications. While numerous solutions have been deve…
Estimating the Resize Parameter in End-to-end Learned Image Compression
Li-Heng Chen, Christos G. Bampis, Zhi Li +2
We describe a search-free resizing framework that can further improve the rate-distortion tradeoff of recent learned image compression models. Our approach is simple: compose a pai…
Convolutional Block Design for Learned Fractional Downsampling
Li-Heng Chen, Christos G. Bampis, Zhi Li +2
The layers of convolutional neural networks (CNNs) can be used to alter the resolution of their inputs, but the scaling factors are limited to integer values. However, in many imag…
Enhancing VMAF through New Feature Integration and Model Combination
Fan Zhang, Angeliki Katsenou, Christos Bampis +3
VMAF is a machine learning based video quality assessment method, originally designed for streaming applications, which combines multiple quality metrics and video features through…
Perceptual Video Quality Prediction Emphasizing Chroma Distortions
Li-Heng Chen, Christos G. Bampis, Zhi Li +2
Measuring the quality of digital videos viewed by human observers has become a common practice in numerous multimedia applications, such as adaptive video streaming, quality monito…
Perceptually Optimizing Deep Image Compression
Li-Heng Chen, Christos G. Bampis, Zhi Li +2
Mean squared error (MSE) and norms have largely dominated the measurement of loss in neural networks due to their simplicity and analytical properties. However, when used…