1 citations · 2 across the 7 of their papers we have counts for
7 papers
MoiréXNet: Adaptive Multi-Scale Demoiréing with Linear Attention Test-Time Training and Truncated Flow Matching Prior
Liangyan Li, Yimo Ning, Kevin Le +4
This paper introduces a novel framework for image and video demoiréing by integrating Maximum A Posteriori (MAP) estimation with advanced deep learning techniques. Demoiréing addre…
PNCS:Power-Norm Cosine Similarity for Diverse Client Selection in Federated Learning
Liangyan Li, Yangyi Liu, Yimo Ning +2
Federated Learning (FL) has emerged as a powerful paradigm for leveraging diverse datasets from multiple sources while preserving data privacy by avoiding centralized storage. Howe…
Gaussian Rate-Distortion-Perception Coding and Entropy-Constrained Scalar Quantization
Li Xie, Liangyan Li, Jun Chen +2
This paper investigates the best known bounds on the quadratic Gaussian distortion-rate-perception function with limited common randomness for the Kullback-Leibler divergence-based…
Deep RAW Image Super-Resolution. A NTIRE 2024 Challenge Survey
Marcos V. Conde, Florin-Alexandru Vasluianu, Radu Timofte +32
This paper reviews the NTIRE 2024 RAW Image Super-Resolution Challenge, highlighting the proposed solutions and results. New methods for RAW Super-Resolution could be essential in…
Output-Constrained Lossy Source Coding With Application to Rate-Distortion-Perception Theory
Li Xie, Liangyan Li, Jun Chen +1
The distortion-rate function of output-constrained lossy source coding with limited common randomness is analyzed for the special case of squared error distortion measure. An expli…
SwinFSR: Stereo Image Super-Resolution using SwinIR and Frequency Domain Knowledge
Ke Chen, Liangyan Li, Huan Liu +3
Stereo Image Super-Resolution (stereoSR) has attracted significant attention in recent years due to the extensive deployment of dual cameras in mobile phones, autonomous vehicles a…
A Data-Centric Solution to NonHomogeneous Dehazing via Vision Transformer
Yangyi Liu, Huan Liu, Liangyan Li +2
Recent years have witnessed an increased interest in image dehazing. Many deep learning methods have been proposed to tackle this challenge, and have made significant accomplishmen…