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20182026
most citedToward Convolutional Blind Denoising of Real Photographs

62 citations · 78 across the 12 of their papers we have counts for

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11 papers · 1 filter

cs.CV2026

DPA: Decoupling Product-Agnostic Anomaly Representations for Zero-shot Anomaly Generation

Hang Yao, Yansheng Fu, Ming Liu +4

Industrial anomaly detection benefits from anomaly samples, yet newly deployed products typically provide only normal images, making anomaly samples difficult to collect. Zero-shot…

cs.CV2024

Retrieval Augmented Image Harmonization

Haolin Wang, Ming Liu, Zifei Yan +3

When embedding objects (foreground) into images (background), considering the influence of photography conditions like illumination, it is usually necessary to perform image harmon…

cs.CV2024

Learning Spatially Decoupled Color Representations for Facial Image Colorization

Hangyan Zhu, Ming Liu, Chao Zhou +3

Image colorization methods have shown prominent performance on natural images. However, since humans are more sensitive to faces, existing methods are insufficient to meet the dema…

cs.CV2024★ 1 cited

Deblur4DGS: 4D Gaussian Splatting from Blurry Monocular Video

Renlong Wu, Zhilu Zhang, Mingyang Chen +2

Recent 4D reconstruction methods have yielded impressive results but rely on sharp videos as supervision. However, motion blur often occurs in videos due to camera shake and object…

cs.CV2024

Combining Generative and Geometry Priors for Wide-Angle Portrait Correction

Lan Yao, Chaofeng Chen, Xiaoming Li +2

Wide-angle lens distortion in portrait photography presents a significant challenge for capturing photo-realistic and aesthetically pleasing images. Such distortions are especially…

cs.CV2024★ 3 cited

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

Hang Yao, Ming Liu, Haolin Wang +4

Diffusion models have shown superior performance on unsupervised anomaly detection tasks. Since trained with normal data only, diffusion models tend to reconstruct normal counterpa…

cs.CV2024★ 1 cited

Exposure Bracketing Is All You Need For A High-Quality Image

Zhilu Zhang, Shuohao Zhang, Renlong Wu +2

It is highly desired but challenging to acquire high-quality photos with clear content in low-light environments. Although multi-image processing methods (using burst, dual-exposur…

cs.CV2022★ 7 cited

Self-Supervised Image Restoration with Blurry and Noisy Pairs

Zhilu Zhang, Rongjian Xu, Ming Liu +2

When taking photos under an environment with insufficient light, the exposure time and the sensor gain usually require to be carefully chosen to obtain images with satisfying visua…

cs.CV2022★ 1 cited

Incorporating Semi-Supervised and Positive-Unlabeled Learning for Boosting Full Reference Image Quality Assessment

Yue Cao, Zhaolin Wan, Dongwei Ren +2

Full-reference (FR) image quality assessment (IQA) evaluates the visual quality of a distorted image by measuring its perceptual difference with pristine-quality reference, and has…

cs.CV2022★ 2 cited

Adaptive Network Combination for Single-Image Reflection Removal: A Domain Generalization Perspective

Ming Liu, Jianan Pan, Zifei Yan +2

Recently, multiple synthetic and real-world datasets have been built to facilitate the training of deep single image reflection removal (SIRR) models. Meanwhile, diverse testing se…

cs.CV2018★ 62 cited

Toward Convolutional Blind Denoising of Real Photographs

Shi Guo, Zifei Yan, Kai Zhang +2

While deep convolutional neural networks (CNNs) have achieved impressive success in image denoising with additive white Gaussian noise (AWGN), their performance remains limited on…