PUBLICATIONS / IIL LAB

以研究，
回应真实的问题。

研究成果 / Selected publications

SELECTED WORK

代表性论文

2025ICCV

工业异常检测 / 多模态

Triad: Empowering LMM-based Anomaly Detection with Vision Expert-guided Visual Tokenizer and Manufacturing Process

Yuanze Li, Shihao Yuan, Haolin Wang, Qizhang Li, Ming Liu, Chen Xu, Guangming Shi, Wangmeng Zuo

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2025CVPR

可控视觉生成

MC^2: Multi-concept Guidance for Customized Multi-concept Generation

Jiaxiu Jiang, Yabo Zhang, Kailai Feng, Xiaohe Wu, Wenbo Li, Renjing Pei, Fan Li, Wangmeng Zuo

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2025CVPR

视频生成

Generative inbetweening through frame-wise conditions-driven video generation

Tianyi Zhu, Dongwei Ren, Qilong Wang, Xiaohe Wu, Wangmeng Zuo

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2025Pattern Recognition

三维视觉 / 增量学习

FILP-3D: Enhancing 3D Few-shot Class-incremental Learning with Pre-trained Vision-Language Models

Wan Xu, Tianyu Huang, Tianyu Qu, Guanglei Yang, Yiwen Guo, Wangmeng Zuo

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2024Pattern Recognition

图像去噪

Flexible image denoising model with multi-layer conditional feature modulation

Jia-Zhi Du, Xin Qiao, Zifei Yan, Hongzhi Zhang, Wangmeng Zuo

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2024ECCV

异常检测 / 扩散模型

GLAD: Towards Better Reconstruction with Global and Local Adaptive Diffusion Models for Unsupervised Anomaly Detection

Hang Yao, Ming Liu, Haolin Wang, Zhicun Yin, Zifei Yan, Xiaopeng Hong, Wangmeng Zuo

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2018CVPR Workshops

图像复原

Multi-Level Wavelet-CNN for Image Restoration

Pengju Liu, Hongzhi Zhang, Kai Zhang, Liang Lin, Wangmeng Zuo

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2018IEEE Transactions on Image Processing

图像去噪

FFDNet: Toward a Fast and Flexible Solution for CNN based Image Denoising

Kai Zhang, Wangmeng Zuo, Lei Zhang

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MORE PUBLICATIONS

以研究，回应真实的问题。

代表性论文

Triad: Empowering LMM-based Anomaly Detection with Vision Expert-guided Visual Tokenizer and Manufacturing Process

MC^2: Multi-concept Guidance for Customized Multi-concept Generation

Generative inbetweening through frame-wise conditions-driven video generation

FILP-3D: Enhancing 3D Few-shot Class-incremental Learning with Pre-trained Vision-Language Models

Flexible image denoising model with multi-layer conditional feature modulation

GLAD: Towards Better Reconstruction with Global and Local Adaptive Diffusion Models for Unsupervised Anomaly Detection

Multi-Level Wavelet-CNN for Image Restoration

FFDNet: Toward a Fast and Flexible Solution for CNN based Image Denoising

更多研究成果

以研究，
回应真实的问题。