most citedSemantic Image Attack for Visual Model Diagnosis

1 citations · 2 across the 4 of their papers we have counts for

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cs.CV2024

BrainDreamer: Reasoning-Coherent and Controllable Image Generation from EEG Brain Signals via Language Guidance

Ling Wang, Chen Wu, Lin Wang

Can we directly visualize what we imagine in our brain together with what we describe? The inherent nature of human perception reveals that, when we think, our body can combine lan…

cs.CV20241 cited

Review Learning: Advancing All-in-One Ultra-High-Definition Image Restoration Training Method

Xin Su, Zhuoran Zheng, Chen Wu

All-in-one image restoration tasks are becoming increasingly important, especially for ultra-high-definition (UHD) images. Existing all-in-one UHD image restoration methods usually…

cs.CV202415 cited

U-shaped Vision Mamba for Single Image Dehazing

Zhuoran Zheng, Chen Wu

Currently, Transformer is the most popular architecture for image dehazing, but due to its large computational complexity, its ability to handle long-range dependency is limited on…

cs.CV2023

PATMAT: Person Aware Tuning of Mask-Aware Transformer for Face Inpainting

Saman Motamed, Jianjin Xu, Chen Henry Wu +1

Generative models such as StyleGAN2 and Stable Diffusion have achieved state-of-the-art performance in computer vision tasks such as image synthesis, inpainting, and de-noising. Ho…

cs.CV2023

Zero-shot Model Diagnosis

Jinqi Luo, Zhaoning Wang, Chen Henry Wu +2

When it comes to deploying deep vision models, the behavior of these systems must be explicable to ensure confidence in their reliability and fairness. A common approach to evaluat…

cs.CV20231 cited

Semantic Image Attack for Visual Model Diagnosis

Jinqi Luo, Zhaoning Wang, Chen Henry Wu +2

In practice, metric analysis on a specific train and test dataset does not guarantee reliable or fair ML models. This is partially due to the fact that obtaining a balanced, divers…