collaborators

9 papers

cs.CV2026

The First Challenge on Remote Sensing Infrared Image Super-Resolution at NTIRE 2026: Benchmark Results and Method Overview

Kai Liu, Haoyang Yue, Zeli Lin +65

This paper presents the NTIRE 2026 Remote Sensing Infrared Image Super-Resolution (x4) Challenge, one of the associated challenges of NTIRE 2026. The challenge aims to recover high…

cs.CV2026

The First Challenge on Mobile Real-World Image Super-Resolution at NTIRE 2026: Benchmark Results and Method Overview

Jiatong Li, Zheng Chen, Kai Liu +91

This paper provides a review of the NTIRE 2026 challenge on mobile real-world image super-resolution, highlighting the proposed solutions and the resulting outcomes. The challenge…

cs.CV2026

The Fourth Challenge on Image Super-Resolution (4) at NTIRE 2026: Benchmark Results and Method Overview

Zheng Chen, Kai Liu, Jingkai Wang +150

This paper presents the NTIRE 2026 image super-resolution (4) challenge, one of the associated competitions of the NTIRE 2026 Workshop at CVPR 2026. The challenge aims to r…

cs.CV2026

BinaryDemoire: Moiré-Aware Binarization for Image Demoiréing

Zheng Chen, Zhi Yang, Xiaoyang Liu +5

Image demoiréing aims to remove structured moiré artifacts in recaptured imagery, where degradations are highly frequency-dependent and vary across scales and directions. While rec…

cs.CV2025

RIFLE: Removal of Image Flicker-Banding via Latent Diffusion Enhancement

Libo Zhu, Zihan Zhou, Xiaoyang Liu +4

Capturing screens is now routine in our everyday lives. But the photographs of emissive displays are often influenced by the flicker-banding (FB), which is alternating bright%u2013…

cs.CV2025

QuantDemoire: Quantization with Outlier Aware for Image Demoiréing

Zheng Chen, Kewei Zhang, Xiaoyang Liu +4

Demoiréing aims to remove moiré artifacts that often occur in images. While recent deep learning-based methods have achieved promising results, they typically require substantial c…

cs.CV2025

FideDiff: Efficient Diffusion Model for High-Fidelity Image Motion Deblurring

Xiaoyang Liu, Zhengyan Zhou, Zihang Xu +3

Recent advancements in image motion deblurring, driven by CNNs and transformers, have made significant progress. Large-scale pre-trained diffusion models, which are rich in real-wo…

cs.CV2025

Freqformer: Image-Demoiréing Transformer via Effective Frequency Decomposition

Xiaoyang Liu, Bolin Qiu, Zheng Chen +5

Image demoiréing remains a challenging task due to the complex interplay between texture corruption and color distortions caused by moiré patterns. Existing methods, especially tho…

cs.CV2025

One-Step Diffusion Model for Image Motion-Deblurring

Xiaoyang Liu, Yuquan Wang, Zheng Chen +4

Currently, methods for single-image deblurring based on CNNs and transformers have demonstrated promising performance. However, these methods often suffer from perceptual limitatio…