43 citations · 56 across the 11 of their papers we have counts for
7 papers · 1 filter
Voyaging into Perpetual Dynamic Scenes from a Single View
Fengrui Tian, Tianjiao Ding, Jinqi Luo +2
The problem of generating a perpetual dynamic scene from a single view is an important problem with widespread applications in augmented and virtual reality, and robotics. However,…
Unsupervised Model Diagnosis
Yinong Oliver Wang, Eileen Li, Jinqi Luo +2
Ensuring model explainability and robustness is essential for reliable deployment of deep vision systems. Current methods for evaluating robustness rely on collecting and annotatin…
Contextual Knowledge Pursuit for Faithful Visual Synthesis
Jinqi Luo, Kwan Ho Ryan Chan, Dimitris Dimos +1
Modern text-to-vision generative models often hallucinate when the prompt describing the scene to be generated is underspecified. In large language models (LLMs), a prevalent strat…
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…
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…
Inconspicuous Adversarial Patches for Fooling Image Recognition Systems on Mobile Devices
Tao Bai, Jinqi Luo, Jun Zhao
Deep learning based image recognition systems have been widely deployed on mobile devices in today's world. In recent studies, however, deep learning models are shown vulnerable to…
Generating Adversarial yet Inconspicuous Patches with a Single Image
Jinqi Luo, Tao Bai, Jun Zhao
Deep neural networks have been shown vulnerable toadversarial patches, where exotic patterns can resultin models wrong prediction. Nevertheless, existing ap-proaches to adversarial…