Publications & Patents
Academic Publications
Enhancing HEVC Compressed Videos with a Partition-Masked Convolutional Neural Network
He, Xiaoyi, et al.
Abstract
We propose a novel partition-masked convolutional neural network (CNN) that utilizes partition information in video encoder to enhance compressed videos. Achieved approximately 10% bitrate savings on benchmark sequences.
Partition-aware Adaptive Switching Networks for Post-processing in HEVC
Lin, Weiyao, He, Xiaoyi, et al.
Abstract
We introduce an adaptive-switching neural network (ASN) that consists of multiple independent CNNs to adaptively handle the variations in content and distortion within compressed video frames, further reducing visual artifacts.
Key-point Sequence Lossless Compression for Intelligent Video Analysis
Lin, Weiyao, He, Xiaoyi, et al.
Abstract
This paper presents a lossless compression method for key-point sequences in videos to enable efficient intelligent video analysis.
A Multimodal Lossless Coding Method for Skeletons in Videos
He, Xiaoyi, et al.
Abstract
This paper presents a lossless compression method for skeleton data in videos based on spatial and temporal correlation, achieving about 84% compression ratio on test surveillance sequences.
Adaptive Lossless Compression of Skeleton Sequences
Lin, Weiyao, Shinde, TS, Dai, Wenrui, Liu, Ming, He, Xiaoyi, et al.
Abstract
An adaptive compression framework for skeleton data that dynamically selects optimal coding methods based on data characteristics.
Patents
Image Illumination Compensation Method and System Based on Tone Shift Estimation and Point-by-Point Tone Mapping
He, Xiaoyi; et al.
Abstract
An image illumination compensation method based on tone shift estimation and point-by-point tone mapping. The system extracts tone shift and mapping functions from calibration charts to perform illumination compensation on images, providing superior results compared to traditional gamma correction methods.
Convolutional Neural Network-based In-Loop Filtering Method and System for Video Coding and Decoding
Lin, Weiyao; He, Xiaoyi
Abstract
A method and system for in-loop filtering in video coding and decoding based on convolutional neural networks. The method uses CNN models to enhance the quality of compressed video frames within the coding loop, reducing compression artifacts while maintaining coding efficiency.
Generative Adversarial Network-based In-Loop Filtering Method and System for Video Coding and Decoding
Lin, Weiyao; He, Xiaoyi
Abstract
A method and system for in-loop filtering in video coding and decoding based on generative adversarial networks (GAN). The approach uses a GAN architecture with generator and discriminator models to improve the quality of reconstructed video frames within the coding loop, providing better visual quality than traditional CNN methods.
In-Loop Filtering Implementation Method Based on Joint Construction and Adaptive Selection of Multiple Networks
Lin, Weiyao; He, Xiaoyi; et al.
Abstract
A method for implementing in-loop filtering in video coding based on joint construction and adaptive selection of multiple neural networks. The system dynamically selects the optimal filtering network based on content characteristics, offering improved video quality with adaptive processing.