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20232026
most citedGLAD: Towards Better Reconstruction with Global and Local Adaptive Diffusion Models for Unsupervised Anomaly Detection

3 citations · 7 across the 22 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

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★ 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

LLM as a Complementary Optimizer to Gradient Descent: A Case Study in Prompt Tuning

Zixian Guo, Ming Liu, Zhilong Ji +3

Mastering a skill generally relies on both hands-on experience from doers and insightful, high-level guidance by mentors. Will this strategy also work well for solving complex non-…

cs.CV2024

SmartControl: Enhancing ControlNet for Handling Rough Visual Conditions

Xiaoyu Liu, Yuxiang Wei, Ming Liu +4

Human visual imagination usually begins with analogies or rough sketches. For example, given an image with a girl playing guitar before a building, one may analogously imagine how…