Search Results for author: Jiwen Yu

Found 6 papers, 5 papers with code

DiffLLE: Diffusion-guided Domain Calibration for Unsupervised Low-light Image Enhancement

no code implementations18 Aug 2023 Shuzhou Yang, Xuanyu Zhang, Yinhuai Wang, Jiwen Yu, YuHan Wang, Jian Zhang

Specifically, we adopt a naive unsupervised enhancement algorithm to realize preliminary restoration and design two zero-shot plug-and-play modules based on diffusion model to improve generalization and effectiveness.

Denoising Low-Light Image Enhancement

CRoSS: Diffusion Model Makes Controllable, Robust and Secure Image Steganography

1 code implementation26 May 2023 Jiwen Yu, Xuanyu Zhang, Youmin Xu, Jian Zhang

Current image steganography techniques are mainly focused on cover-based methods, which commonly have the risk of leaking secret images and poor robustness against degraded container images.

Image Steganography

FreeDoM: Training-Free Energy-Guided Conditional Diffusion Model

1 code implementation ICCV 2023 Jiwen Yu, Yinhuai Wang, Chen Zhao, Bernard Ghanem, Jian Zhang

In this work, we propose a training-Free conditional Diffusion Model (FreeDoM) used for various conditions.

Face Detection

Unlimited-Size Diffusion Restoration

1 code implementation1 Mar 2023 Yinhuai Wang, Jiwen Yu, Runyi Yu, Jian Zhang

Our simple, parameter-free approaches can be used not only for image restoration but also for image generation of unlimited sizes, with the potential to be a general tool for diffusion models.

Image Generation Image Restoration

Zero-Shot Image Restoration Using Denoising Diffusion Null-Space Model

2 code implementations1 Dec 2022 Yinhuai Wang, Jiwen Yu, Jian Zhang

Most existing Image Restoration (IR) models are task-specific, which can not be generalized to different degradation operators.

Colorization Deblurring +7

GAN Prior based Null-Space Learning for Consistent Super-Resolution

1 code implementation24 Nov 2022 Yinhuai Wang, Yujie Hu, Jiwen Yu, Jian Zhang

Consistency and realness have always been the two critical issues of image super-resolution.

Image Super-Resolution

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