62 citations · 78 across the 12 of their papers we have counts for
12 papers
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
Flexible Image Denoising with Multi-layer Conditional Feature Modulation
Jiazhi Du, Xin Qiao, Zifei Yan +2
For flexible non-blind image denoising, existing deep networks usually take both noisy image and noise level map as the input to handle various noise levels with a single model. Ho…
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…