8 citations · 23 across the 6 of their papers we have counts for
11 papers
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…
Banding vs. Quality: Perceptual Impact and Objective Assessment
Lukáš Krasula, Zhi Li, Christos G. Bampis +3
Staircase-like contours introduced to a video by quantization in flat areas, commonly known as banding, have been a long-standing problem in both video processing and quality asses…
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…
Strategy for Boosting Pair Comparison and Improving Quality Assessment Accuracy
Suiyi Ling, Jing Li, Anne Flore Perrin +3
The development of rigorous quality assessment model relies on the collection of reliable subjective data, where the perceived quality of visual multimedia is rated by the human ob…
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…