6 papers
A Feature Shuffling and Restoration Strategy for Universal Unsupervised Anomaly Detection
Wei Luo, Haiming Yao, Zhenfeng Qiang +2
Unsupervised anomaly detection is vital in industrial fields, with reconstruction-based methods favored for their simplicity and effectiveness. However, reconstruction methods ofte…
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 r…
Combined Flicker-banding and Moire Removal for Screen-Captured Images
Libo Zhu, Zihan Zhou, Zhiyi Zhou +5
Capturing display screens with mobile devices has become increasingly common, yet the resulting images often suffer from severe degradations caused by the coexistence of moiré pat…
VEQ: Modality-Adaptive Quantization for MoE Vision-Language Models
Guangshuo Qin, Zhiteng Li, Zheng Chen +3
Mixture-of-Experts(MoE) Vision-Language Models (VLMs) offer remarkable performance but incur prohibitive memory and computational costs, making compression essential. Post-Training…
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…
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…